To understand users’ digital media behaviors, sport communication scholarship has often embraced the lens of uses and gratifications (U&G) theory (Abeza et al., 2015; Li et al., 2019; Zeren et al., 2022). Given that U&G theory assumes an active, goal-directed approach to media selection and consumption (Katz et al., 1973), sport communication scholarship has identified motives of sport social media usage broadly (e.g., Clavio & Frederick, 2014) by platforms such as Facebook (e.g., Sanderson, 2013), Twitter (e.g., Witkemper et al., 2012), and social live streaming services (Kim & Kim, 2020). This has resulted in a plethora of motivational factors summarized by Filo et al. (2015) as interactivity, information gathering, entertainment, fandom, and camaraderie, with more recent scholarship continuing to embrace these motives (e.g., Li et al., 2019). While informative, this line of scholarship has often employed U&G theory despite its controversies or criticisms (Li et al., 2019), often without acknowledging its critics or competing perspectives on media consumption.
U&G theory has been criticized for overstating the purposefulness of consumers (White, 1994). Meanwhile, competing theories and emerging research suggest media use can be habitual and unconscious in nature (e.g., Diddi & LaRose, 2006; Hofmann et al., 2009; Hu et al., 2021; LaRose et al., 2003). In particular, general communication scholarship has found evidence of unintentional social media use, often becoming a part of daily routines (e.g., Ahmed & Zia, 2022; Giannakos et al., 2013). This is particularly true for more experienced media users who likely rely on habit and routines with respect to social media behaviors, compared to newer users (Lee & Ma, 2012). Thus, despite often being ignored by U&G framed studies (Chiu & Huang, 2015), research suggests habit may be an important driver of media usage. Yet, habit has often been overlooked among sport communication scholars (see Filo et al., 2015) including in recent scholarship (e.g., Kim & Kim, 2020; Li et al., 2019).
Despite often being overlooked, there are indications of habit within sport media use. For instance, limited studies (viz., Billings et al., 2019; Lewis et al., 2017) have considered habitual use as a motive for media use. Moreover, there is evidence of sport consumers using the scan-and-shift style of media attention (Jensen et al., 1997), such as using social media with other media including streaming (Collins et al., 2016) and television (TV; Gibbs et al., 2014; Lewis et al., 2021) as well as being passive and using platforms to lurk rather than post content (Walker et al., 2017), that is particularly likely to develop for those engaging in habitual media use (Irwin, 2017). Effectively, between evidence of habitual use within general media use scholarship and behavioral patterns that suggest habitual use among sport consumers, it is likely that sport consumers have evolved to use social media habitually.
Thus, the purpose of this research is to explore how sport consumers use social media, with a particular emphasis on understanding whether social media consumption can be more unconscious and habitual than implied by U&G theory and sport communication research embracing the U&G perspective. Taking a critical approach to the use of U&G theory helps further this body of social media scholarship that has been plagued by a lack of rigorous utilization of theory (Abeza & Sanderson, 2022). A series of semistructured interviews were conducted with 22 social media users with varying levels of fandom and social media usage behaviors. Five themes were found pertaining to how consumers use social media: passively, distinctly, periodically, habitually, and universally. Results indicate that social media usage was largely habitual with tasks performed as part of a routine driven by learned patterns of behavior and preferences rather than purposefully seeking out and rationally evaluating platforms. In addition, social media usage was primarily passive, consisting of lurking and scrolling, with limited content creation. Moreover, findings indicate that consumption related to sport content was consistently used in tandem with other content types, and that fandom failed to drive or influence behaviors. This research contributes theoretically by highlighting a type of social media behavior, namely, habitual and unconscious rather than driven and purposeful, thereby informing our approaches and assumptions about social media usage among sport consumers.
Literature Review
U&G Theory
In response to a struggling communication field and an understanding that there was more to mass communication than persuasion, the question “what do people do with media?” arose (Katz, 1959). Lasswell (1948) originally proposed that media facilitated the fulfillment of four functions, namely, diversion, personal relationships, personal identity, and surveillance (McQuail et al., 1972). This idea, combined with evidence of TV ratings (i.e., if consumers did not like a show, they did not watch it), inspired the notion that consumers are active (i.e., deliberate and purposeful) in their media consumption. This approach centers around the idea that media is only useful when consumers have use for it in the social and psychological context in which it lives (Katz, 1959). Thus, U&G theory is grounded in the notion that individuals select media based on satisfying a need and only continue media usage so long as that need continues to be satisfied (Katz et al., 1973). Moreover, individuals select the optimal media available based on their current needs. Effectively, the theory is built on two assumptions: Consumers are (a) purposeful in the selection of the media they consume, and (b) aware of their reasons for selecting different media options.
New media, including Web 1.0, Web 2.0, and social media, gave credibility to U&G theory, as they provided a wider range of media types and sources from which to select media (Ruggiero, 2000). The internet is the ultimate example of individualism, as it allows consumers to select the content they view/create (Singer, 1998). The internet’s interactive nature lent itself well to U&G theory, while other communication theories struggled to adapt to technological advances (Ruggiero, 2000).
Based on this resurgence, U&G theory was applied across new media settings such as mobile phones (Leung & Wei, 2000), text messaging (Grellhesl & Punyanunt-Carter, 2012), the internet (Stafford et al., 2004), social media (Whiting & Williams, 2013), and online gaming (Wu et al., 2010). Given the focus of the theory (i.e., purposeful media selection based on evaluation of uses/gratifications; Katz et al., 1973), research with a U&G approach often focuses on the motivational perspective, asking why consumers use a media resulting in a myriad of lists of motivations across studies depending on the technology and context considered. With respect to social media usage, general scholarship has identified a range of motives including social interaction, pass time, information seeking, entertainment, relaxation, communicatory utility, convenience utility, expression of opinion, information sharing, and surveillance/knowledge about others (Whiting & Williams, 2013). Similarly, to examine the nature of sport digital media, U&G theory has been broadly employed (Li et al., 2019).
Sport Social Media Motivation Scholarship
U&G theory has frequently been used within sport communication scholarship (Abeza & Sanderson, 2022; Moore, 2018). Building on the assumptions of U&G theory, scholars have identified motives that trigger sport social media usage, often through online surveys with respondents rating the degree to which they agree with a prescriptive list of motives across social media platforms and sport contexts (e.g., Billings et al., 2019; Lewis et al., 2017; Li et al., 2019; Tang et al., 2022). For example, researchers have investigated motives related to general social media use (e.g., Larkin & Fink, 2016; Lewis et al., 2017) and platform-specific use including Twitter (e.g., Frederick et al., 2012; Witkemper et al., 2012), fan community sites (e.g., Walker et al., 2017), Facebook groups (e.g., Sanderson, 2013), and social live streaming services (e.g., Kim & Kim, 2020). Researchers have also examined multiple platforms concurrently (e.g., Fenton et al., 2021; Gibbs et al., 2014; Wakefield, 2016) or various news media concurrently (e.g., Moore, 2018), and compared platforms and cultures (e.g., Billings et al., 2017; Li et al., 2019; Tang et al., 2022). A variety of sport contexts have also been investigated including following general sport content (e.g., Billings et al., 2017; Kim & Kim, 2020), women’s sports (e.g., Fenton et al., 2021; Tang et al., 2022), and following specific accounts such as accounts of athletes in general (e.g., Witkemper et al., 2012), specific athletes (e.g., Clavio & Kian, 2010; Frederick et al., 2012), sport teams (e.g., Gibbs et al., 2014; Li et al., 2019; Popp & Woratschek, 2016; Walker et al., 2017), and sport organizations (e.g., Hambrick & Svensson, 2015).
This research has provided valuable insight on a myriad of motives for sport social media usage within specific contexts. For example, Li et al. (2019) compared the strength of the motives of information, entertainment, technical knowledge, team support, pastime, and escape between Chinese Weibo users and American Twitter users with respect to the NBA (National Basketball Association) Lakers organization. Billings et al. (2019) and Lewis et al. (2017) evaluated 12 motives of social media consumption, namely, arousal, passing time, camaraderie, entertainment, self-expression, habitual use, information surveillance, escape, building a virtual community, companionship, coolness, and maintaining relationships, while Tang et al. (2022) considered how the motives of entertainment, self-esteem, escape, group affiliation, and esthetic impacted TV and digital media consumption, finding differences between Chinese, German, and American respondents. Effectively, while there is no set list of motivations used across studies, unsurprising given U&G theory has been criticized for the motivations being more dependent on researchers’ than participants’ input (see Footnote 1), more recent scholarship frequently considers motives aligned with those in earlier scholarship (e.g., Clavio & Frederick, 2014; Clavio & Kian, 2010; Frederick et al., 2012; Gibbs et al., 2014) aptly summarized by Filo et al. (2015) as interactivity, information gathering, entertainment, fandom, and camaraderie.
U&G Theory Criticisms and Competing Perspectives on Behavior
The aforementioned scholarship provides valuable insight into why sport consumers use social media but has largely failed to acknowledge a criticism of U&G theory1 and competing perspectives on media behavior. In other words, in both general media and sport communication scholarship, U&G theory has been employed despite its controversy among scholars (Chiu & Huang, 2015; Li et al., 2019). A criticism of U&G theory is that it overstates the purposefulness of consumers (White, 1994). Rather than purposeful, goal-driven approaches to consumption, competing perspectives acknowledge habit can be a key driver of media consumption (Diddi & LaRose, 2006; LaRose et al., 2003). Competing scholarship suggests media consumption is predominantly automatic (i.e., not consciously controlled) in nature, often determined by the impulsive system (LaRose, 2010). Under the impulsive system, behavioral tendencies emerge over time, resulting in cues signaling specific reactions (Hofmann et al., 2009). Consequently, with continued usage, media behavior becomes automatic and habitually performed without deliberation, self-appraisal, goal setting, or judgment (Diddi & LaRose, 2006).
U&G theory essentially assumes users are conscious in their technology selection, wherein they rationally evaluate the benefits and costs of media use and select accordingly. In particular, there are rational factors users identify and evaluate when selecting media (Katz et al., 1973; Li et al., 2019). Yet, in making the assumption that social media selection is guided by conscious evaluations of rational factors, we omit that human decision making, including decisions pertaining to social media use, involves nonrational, unconscious factors including habit (Ortiz de Guinea & Markus, 2009). Approaches based on evaluations of rational factors preceding media use fail to account for habits developed from continued media usage. However, habit has been identified as a key reason for media consumption (LaRose et al., 2003).
Emergent research has found that as users develop habits with respect to social media use, their conscious evaluations of social media attributes diminish (Hu et al., 2018, 2021). As media usage continues and becomes a habit, the habit is the only driving factor that matters; people do not perform a deliberate cost–benefit analysis but rather use social media habitually for efficiency, simplicity, and convenience (Hu et al., 2018, 2021; Limayem et al., 2007). Thus, habits can help decrease the time and cognitive effort dedicated to making decisions related to media use (Chiu & Huang, 2015). More emphasis should be placed on nonreasoned, unplanned action rather than planned, reasoned action, with respect to continued use of technology, such as social media (Ortiz de Guinea & Markus, 2009). Since “habitual users assess value of social media in a more unconscious, automatic manner” (Hu et al., 2021, p. 142), a competing approach to perspectives derived in rational choice is that habit dictates usage behavior.
Evidence of a habitual approach to media use challenges existing perspectives such as U&G theory; once individuals realize they can get their “daily news fix” better from X than Y, “they quickly stop agonizing over the news selection decision from day to day and moment to moment, as the U&G paradigm insists they should” (Diddi & LaRose, 2006, p. 195). Instead, individuals have media habits, or fall into patterns of repeated media behavior, and do not engage in active self-observation. There is emerging support for habitual behavior among media users (e.g., Griffiths, 2018; Griffiths & Kuss, 2019; Hu et al., 2021), with Wood et al. (2002) finding that over half of media use is habitual in nature. Communication scholarship has found that individuals use social media unintentionally, with it often being a part of their daily routines (e.g., Ahmed & Zia, 2022; Giannakos et al., 2013). This is particularly true for more experienced social media users, who likely rely on habit and routines with respect to social media behaviors compared to newer users (Lee & Ma, 2012). Furthermore, habitual use has been incorporated into research seeking to explore social media behaviors such as getting deceived on social media (Vishwanath, 2015) and social media self-control failure (Du et al., 2019). Thus, despite often being ignored by U&G framed studies (Chiu & Huang, 2015), general (social) media use research suggests habit may be an important driver of media usage.
Apart from Billings et al. (2019) and Lewis et al. (2017) who considered it as a motive of media use, habitual use has not been considered with respect to sport social media usage (e.g., Clavio & Kian, 2010; Fenton et al., 2021; Frederick et al., 2012; Kim & Kim, 2020; Li et al., 2019; Tang et al., 2022). The identification of habit as an important driver of general media usage indicates that sport communication scholarship should consider whether habits have formed for sport consumers. Moreover, the overwhelming use of U&G theory among sport social media scholarship coupled with the scholarship’s focus on motivation identification implies a narrative of purposeful, goal-directed, nonhabitual social media usage. Given the time that has lapsed since first adoption and introduction into our scholarship (e.g., Pegoraro, 2010) coupled with the fact that media habits develop overtime (Diddi & LaRose, 2006; Lee & Ma, 2012), it is important to consider the possibility that habits have formed over the past decade, which now dictate usage behavior. Thus, research is required to explore whether sport social media usage can be habitual rather than universally purposeful as implied by our scholarship.
Sport Social Media Consumption
Social media can enhance the sport experience as it serves as a complementary medium to other consumption experiences (Kassing & Sanderson, 2010). Sport social media consumption often occurs concurrently with other sport behaviors including playing fantasy sport (Larkin & Fink, 2016; Weiner & Dwyer, 2017), streaming content (Collins et al., 2016), and watching TV (Gibbs et al., 2014; Lewis et al., 2021) and live games (Uhrich, 2014). When social media is used in tandem with live sport consumption via TV, it is being used for both game-related and game-unrelated activities (Lewis et al., 2021). Evidence of sport social media use often being in addition to other behaviors is consistent with evidence that habitual behavior, compared to nonhabitual, is more likely to be associated with unrelated thoughts as its routine nature allows for less cognitive involvement by the user (Wood et al., 2002).
Sport communication scholarship indicates that fans are less likely to engage with hashtags (O’Hallarn et al., 2018). Rather, sport fans tend to lurk on social media, in lieu of actively posting (Walker et al., 2017). This was consistent with an early investigation into college sport fans that found low participation rates on official Twitter and Facebook pages (Clavio & Walsh, 2014). Low levels of engagement with sport social media may be indicative of a more routine, habitual behavior as passively scrolling is less demanding than actively (co-)creating and engaging with content. It also likely aligns with the scan-and-shift style of attention, where heavy media users develop a tendency to scan over content and shift to new content in lieu of dedicating substantial attention to individual pieces of content (Jensen et al., 1997). This attention pattern is particularly likely to develop for those who engage in habitual media use (Irwin, 2017). Effectively, this less purposeful, passive use of social media runs contrary to the high motivation levels implied in our motivation-focused sport communication scholarship, often employing U&G theory.
In summary, existing sport communication scholarship implies sport social media users are highly motivated and active in their social media usage given the focus on and use of U&G theory without consideration to its criticisms nor competitive perspectives. It overlooks the potential that U&G theory can overestimate users’ purposefulness and fails to consider competing theories and perspectives that identify a routine, habitual type of social media use. It also fails to capture insight from general communication scholarship that has identified habit as a key driver of media use (Diddi & LaRose, 2006; LaRose et al., 2003), including social media use (e.g., Ahmed & Zia, 2022; Giannakos et al., 2013). In turn, there is the potential that by failing to consider competing perspectives to U&G theory, sport communication scholarship overstates the activeness and purposefulness of social media users. To investigate this, we pose the following research question: How is sport social media used by sport consumers? While a simplistic question, the answer is complex and nuanced requiring in-depth insight on behavioral tasks performed when using sport social media.
Methods
Given the nature of the research question, namely, seeking to understand in depth the nuances within social media experiences, a qualitative approach was necessary. The research purpose and scope sought to “provide a rich, contextualized understanding” (p. 1451) of how sport social media is used by sport consumers or that which is often the goal of most qualitative studies (Polit & Beck, 2010). In particular, “the purpose of qualitative research has, thus, been directed toward providing in-depth explanations and meanings” (Carminati, 2018, p. 2094), which directly aligns with the research question and goal of this study. A qualitative approach was necessary to be able to describe and rationally critique descriptions of actions, namely, social media usage, within their social context (Kemmis, 1980) as well as discover meaning and understanding (Myers, 2000). In addition to the alignment between a qualitative paradigm and the research scope and purpose, a qualitative approach was chosen to ensure the rigorous application of theory required in social media scholarship (Abeza & Sanderson, 2022). It was beneficial to embrace an inductive, qualitative approach given the conflicting body of scholarship with respect to rational evaluation of media versus unconscious habitual use as it ensured the findings reflected the actions and experiences of the participants. Unlike prior scholarship employing U&G theory that has been criticized for being more dependent on the researchers’ input than that of the participants (Ruggiero, 2000), employing a qualitative paradigm, which “aims to understand the social world from the viewpoint of the respondents” (Myers, 2000, p. 2), attempted to ensure that the findings reflected participants’ experiences and thus answered the research question. Effectively, though all research approaches have limitations and trade-offs (see Limitations and Future Directions section), a critical evaluation of the research purpose and scope indicated that a qualitative approach was appropriate.
Interviews were selected as they are particularly adept at uncovering the story behind participants’ experiences and capturing their viewpoints on a given topic (Turner & Hagstrom-Schmidt, 2022). In particular, “small qualitative studies can gain a more personal understanding of the phenomenon and the results can potentially contribute valuable knowledge” (Myers, 2000, p. 3), with interviews having the potential to ascertain rich, detailed insights into behaviors and decision making. Self-reported observations were considered as a potential approach but were ruled out because (a) self-reports of media usage levels are rarely found to be accurate reflections of actual usage (Parry et al., 2021), and (b) they would be unable to provide the in-depth discussion of meaning behind the experiences that interviews could provide. While interviews also rely on self-reports, given the research question was focused on unearthing insights into the meaning behind experiences rather than accurately recounting media usage levels, we maintain the appropriateness of interviews as the research approach. Given the research question’s focus on social media usage and sport, we sought and considered participants who used social media as consumers rather than content creators and had an interest in sport, though a range of usage levels and sport fandom levels were intentionally captured. It is important to note that this study was delimited to English-speaking adults within the United States and Canada given the cultural differences with respect to social media (Billings et al., 2019; Li et al., 2019; Tang et al., 2022).
Data Generation
Participants were recruited through a combination of purposeful and snowball sampling techniques. By announcing the call for participants on social media, participants volunteered for the study. Since they saw the call on social media, they were social media users and thus would be able to provide insight with respect to the research question. Subsequently, snowball sampling was used to collect participants with a variety of online presences, not just highly engaged users connected to the researchers on social media. To collect a diverse set of participants from a variety of locations across Canada and the United States, phone interviews were used. This approach allowed participants from a wide geographic range to be interviewed and provided flexibility regarding scheduling of interviews (Hanna, 2012).
Between April 2, 2020 and April 20, 2020, we interviewed 22 social media users (11 men and 11 women) between the ages of 20 and 44 years for an average of 31 min. Despite achieving theoretical saturation at approximately 15 participants, additional interviews were conducted to ensure a diverse sample and confirm that saturation was achieved.2 Participants were recruited who followed a range of sports (e.g., professional leagues and niche sports), had a range of fandom levels (e.g., casual fans to hardcore fans), were a range of ages (e.g., older and traditional social media users), had a range of careers (e.g., both inside and outside of the sport industry), and had a range of social media habits (e.g., lurking only to frequently posting, many vs. few accounts, etc.). Table 1 contains participant profiles.
Participant Profiles
| ID | Pseudonym | Gender | Daily social media (hr) | Platforms used (approximate proportion of time per platform in percentages) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Snapchat | TikTok | |||||||||||
| 1 | Dillion | Male | 1 | 8 | 25 | 67 | ||||||
| 2 | Jimmy | Male | 3.5 | 14 | 29 | 58 | ||||||
| 3 | Lincoln | Male | 8–11 | 33a | 33 | 33 | ||||||
| 4 | Sally | Female | 4.5 | <5 | 33 | 11a | 33a | 22 | ||||
| 5 | Noah | Male | 3 | 11a | 67 | 22 | ||||||
| 6 | Lucas | Male | 3.2 | 5 | 63a | <5 | 32 | |||||
| 7 | Dixie | Female | 2.2 | 30 | 60 | 5a | 5a | |||||
| 8 | Mia | Female | 1.5 | 22a | 78 | |||||||
| 9 | Olivia | Female | 3-4 | 5a | 60 | 15a | 15a | 5 | ||||
| 10 | Ben | Male | 2–3 | 20a | 15a | 5 | 60 | |||||
| 11 | Watson | Male | 1–2 | 95 | 5a | |||||||
| 12 | Kylo | Male | 4–5 | 9a | 73a | 12 | 6 | |||||
| 13 | Jaxton | Male | 2.7 | 50 | 50 | |||||||
| 14 | Carson | Male | 1.5 | 5a | 90 | 5 | ||||||
| 15 | Austin | Male | 1 | 90 | 10a | |||||||
| 16 | Evelyn | Female | 4–5 | 30 | 30 | 10a | 10 | 20a | ||||
| 17 | Scarlett | Female | 2 | 30 | 60 | 10 | ||||||
| 18 | Madison | Female | 1–2 | 5 | 40 | 5a | 40 | 5 | ||||
| 19 | Avery | Female | 2–3 | 15 | 20 | 15a | 20a | 30a | 5 | |||
| 20 | Riley | Female | 1 | 67a | 33 | 5 | ||||||
| 21 | Layla | Female | 2 | 30 | 45 | 10a | ||||||
| 22 | Eleanor | Female | 1 | Xa | Xa | Xa | X | Xa | ||||
Note. X indicates usage conditional on notifications; percentages may not add to 100 due to rounding or respondent error. YouTube was not included as no participant used it as a social media platform (e.g., to like, subscribe, comment on, or generate content); rather, usage was limited exclusively to watching videos as a streaming platform.
aPlatform was used to follow little to no sport content.
Semistructured interviews were selected as the data collection technique. There was a core set of questions based on reviews of prior scholarship deemed necessary to ask all participants, and hence, a degree of structure was needed across interviews. Yet, it was anticipated that consumers would have different preferences, habits, and experiences using social media. A standardized interview would make it difficult to identify individual-level nuances. Moreover, semistructured interviews are well suited for perception and opinion exploration on complex issues, and “enable probing for more information and clarification of answers” (Barriball & While, 1994, p. 330). Since this research focused on how users performed behavioral tasks on social media rather than why, an in-depth technique was required.
An interview guide (Table 2) was used followed by probing questions when appropriate (Kvale & Brinkmann, 2009). It was developed to address the research question and was derived from previous sport communication studies on social media (e.g., Billings et al., 2017, 2019; Clavio & Frederick, 2014; Clavio & Kian, 2010; Filo et al., 2015; Frederick et al., 2012; Gibbs et al., 2014; Lewis et al., 2017; Witkemper et al., 2012) as well as in conversations with domain area experts. Prior to data collection, the interview guide was reviewed by subject area experts and a pilot interview was conducted to gather feedback about the questions and process. Afterward, the interview guide was refined to include additional questions to try and tease out nuances between individuals, contexts, and so forth with respect to platform usage (e.g., incorporation of Belk’s [1975] situational variables). After obtaining consent and willingness to participate in the study, the interview began with basic introductory questions to identify social media usage levels before it focused on sport social media usage specifically. This allowed for an understanding of how sport content fits within the broader social media landscape for individuals. Given the emphasis on motivation and U&G theory in prior related literature, the interview then focused on motivational antecedents of social media usage and tried to identify platform-level differences in usage. Finally, the interview concluded by providing participants the opportunity to contribute any additional content they felt relevant or wished to discuss.
Interview Guide Relative to Research Area
| Research area | Interview question(s) |
|---|---|
| Introductory questions | 1. How often do you use social media daily? 2. Which social media sites do you use regularly and how much time daily/weekly do you typically spend on each of these sites? a. How active are you on these sites? |
| Sport social media usage | 3. Do you use social media to follow sports content? a. If so, what type(s) of accounts (e.g., professional organizations, professional sport commentators, other users, trends and hashtags, etc.)? b. Why do you select to follow these accounts and/or hashtags? 4. How do you typically use social media to engage with sport content? 5. When do you typically use social media? Is it used concurrent to other consumption behaviors (e.g., while watching TV)? If so, why do you add social media? 6. What other digital mediums do you use to consume sport content (e.g., websites, watching games on TV, watching news/commentary shows, etc.)? How often do you engage in these behaviors? |
| Motivations of (sport) social media usage | 7. Why do you use social media? a. Why do you use it to access sport content? b. Please describe when and why you access social media solely to view sport content? 8. For each social media platform you use to access sport content, please describe why you use it? Particularly, why do you select one social media platform over another? a. Please explain how your physical surroundings (e.g., geographical location, décor, weather, media, etc.) affect why you select a social media platform. b. Please explain how your social surroundings (e.g., other sport fans present) affect why you select a social media platform. c. Please explain how your temporal perspective (e.g., time of the year, if it is during season vs. out of season, etc.) affects why you select a social media platform. d. Please explain how your task definition (e.g., intent to use social media such as to post vs. to read) affects why you select a social media platform. e. Please explain how your antecedent state (e.g., how you are feeling, if you are tired, need to rant, etc.) affect why you select a social media platform. 9. Please review the following lists of reasons people use social media to access sport content: interactivity, information gathering, entertainment, fandom, and camaraderie. a. Which motives resonate with you? Please explain. b. Which motives do you not agree with or have not personally experienced? Please explain. 10. Can you describe a time in which you used multiple sources/platforms to get information about a sport event/team? If you changed platforms, why? 11. Does your social media platform choice ever depend on what or who you follow on a certain platform? If so, when, why, and how so? 12. What platform features (e.g., newsfeed, stories, etc.) affect your motivation to use a specific platform? Why? a. Does the notion of ephemeral (i.e., temporary content that is not saved or autodeletes) affect your social media usage? Explain. |
| Closing | 13. Are there any additional topics related to our conversation that you wish to discuss? |
Note. Given that the onset of COVID-19 was shortly before our interviews, the above interview guide was developed pre-COVID-19. We intentionally asked participants at the onset of the interview to answer with respect to their behaviors prior to COVID-19, as well as specifically asking them to describe any impact of COVID-19 on their media behaviors.
Data Analysis
The interview and data analysis processes followed precedents of prior scholarship (e.g., Hambrick & Svensson, 2015; Price et al., 2022). The interviews were conducted over the phone and recorded, and notes were taken during the interview. The interviews were transcribed verbatim, with each transcript being compared to the original audio file for verification of accuracy. The data were imported into QSR NVivo 10 to facilitate the coding process. While an inductive formed thematic analysis was used (see Braun & Clarke, 2006), it is relevant to note that the research team’s prior review of relevant literature (e.g., sport communication, U&G theory, and habitual media usage scholarship) may have shaped, at least to some extent, the coding (Smith & McGannon, 2018). Given the exploratory nature of the research question coupled with the conflicting evidence with respect to theory (e.g., habitual media usage vs. U&G theory), we felt an inductive approach was more appropriate than trying to fit the data into a preexisting coding frame. It also allowed for more unanticipated findings or themes beyond the answers to the questions (Braun & Clarke, 2006). The text data were analyzed using the seven-step process outlined by Creswell (2013), as this process encourages transparency in data analysis to support the validity of data generation, while taking into account Braun and Clarke’s (2006) phases of thematic analysis and criteria for good thematic analyses. The initial researcher provided the list of codes and a portion of data to an independent coder to determine whether they would code the data similarly (Gibbs, 2007). Any discrepancies in coding were discussed, reanalyzed, and recoded until Cohen’s kappa coefficient was above .75 (Fleiss et al., 2003). Once coding was completed, interpretation of the research findings was conducted to identify what new information was obtained through the research (Denzin & Lincoln, 2011), with the research team discussing how results are related to the research question and are compared to prior literature (Creswell, 2013).
Data Validity
Given one member of the research team conducted the interviews, the other could be used as an informal peer debriefer throughout the process. Triangulation was used to assess credibility (Krefting, 1991). The convergence of numerous perspectives to achieve mutual confirmation of data ensured all relevant aspects of sport social media usage were investigated (Knafl & Breitmayer, 1989). A version of a stepwise replication technique was employed (Guba, 1981) and a code–recode procedure (where there was at least a 2-week time delay between coding and recoding of data) was used to enhance dependability (Krefting, 1991). Triangulation of multiple data sources, methods, and theoretical perspectives was used to strengthen confirmability (Krefting, 1991). Finally, reflexive analysis was used to ensure the researcher was cognizant of their own influence on the data.
Findings
Five themes were identified with respect to how participants engaged in behavioral tasks associated with social media. These themes were labeled passively (35 mentions), distinctly (19), periodically (22), habitually (13), and universally (34). Each theme is discussed below. We also discuss the interrelation between these themes and how these themes do or do not vary across various participant characteristics such as demographics and fandom levels.
Passively
I don’t post often, if at all, maybe the odd story here and there, but I’m very much on it every day for the reading and the consuming, and the “time-wasting piece.” I do a lot of that, but I don’t contribute back.
Overall, participants did not feel a need to post, often citing a desire to maintain privacy. For example, Layla stated “I just prefer to not have myself all over the Internet.” Additionally, some expressed a lack of confidence in their own content; for example, Evelyn said “I just don’t think people care what I have to say.” Finally, they also expressed that posting was not conducive with their personality or behavior. For example, Carson said “I don’t feel much compulsion to post things.” This finding was consistent across participants regardless of their demographic characteristics (e.g., age, gender, or occupation) and fandom levels. Given that participants who identified highly as fans did not, by and large, feel a need to express that fandom digitally (see Further Probing subsection), it is unsurprising that this theme was consistently dominant across participants. Users did not feel a need to generate content, instead choosing to consume content in a manner more consistent with traditional media featuring curated content. This was captured by Layla who said, “most virtual content that I see is all very curated content” because posting was limited primarily to influencers and professional content generators as opposed to friends and family members on personal accounts.
Participants indicated that rather than interacting with general audiences, if they did interact, it was limited to friends and family and through a private chat function. Noah stated that if he did not know the person, it felt weird to interact with them. Watson said, “I’m not one to try and tag or interact with folks who I don’t really know or the broader community.” Madison explained how she is “more a passive user of social media” and that for her, “interacting with random people online who have the same interest group doesn’t really happen.” For many participants, social media platforms were reduced to their private messaging service, such as using Facebook to access Facebook Messenger. To participants, social media reflected the new reality of communication. This was summarized by Mia who said, “to keep in touch with people, instead of a phone call, you can just hit a like or just comment on their Instagram story and that’s you adding in your two cents for the day.” Though this sentiment was consistent across participants, it was emphasized more so among younger respondents (i.e., below 35 years old).
Periodically
The second theme was the periodic use of social media for brief spans of time. Though social media usage may have totaled a significant amount of time daily, such as Sally estimating 4–5 hr/day, that time was not concentrated. Sally described her usage as “on and off, not straight through, but just throughout the day—like I’ll go on here and scroll.” Austin acknowledged using social media “probably 15 to 20 times daily … say maybe twice an hour for the duration of the time I’m awake,” and Madison stated, “I usually check it when I wake up in the morning, periodically throughout work just for the little mental breaks.”
Across usage levels, participants indicated social media was used predominantly for short spans of time periodically, rather than a single concentrated block of time. Social media was likened to taking a break or passing the time as captured by Evelyn who stated, “if you’re taking a break from work or you get distracted or something, you just scroll through social media.” As the amount of time on social media increased across or within participants (e.g., participants marked an increase in usage at the onset of COVID-19), it often did so by increasing the number of periodic breaks for social media and by lingering longer on social media during those breaks rather than using social media for extended blocks of time. Participants consistently remarked using social media to fill moments of boredom or to take short breaks during the workday regardless of their preferred platforms, overall usage level, or demographic characteristics. It was apparent across participants that habits had formed wherein they would check their social media platforms when they first woke up (e.g., Kylo said “I have to check my Instagram in the morning”) and then for set breaks throughout their workday (e.g., Jaxton said “I have always used social media as a break thing—I would do that even if I were in my office”).
Habitually
I try really hard to be more conscious of it, but I definitely get caught up in that where I’m like, I was doing something or you’ll see a little notification pop up and the next thing you know, it’s been like been minutes and you are still scrolling on Instagram. I’m like, “Damn it. I was doing something productive, and it totally got sidetracked.” There’s definitely a bit of hold that it has, I think, whether we’re trying to be conscious about it or not.
This notion of habitual use ties directly into the prior theme of periodically as many respondents indicated they knew they used social media for breaks throughout the workday but were unable to confidently estimate the number of times they checked it. This was consistent across respondents regardless of their type of employment or location of employment (e.g., working from home or in an office). Some participants went so far as to toy with the notion of addiction, wherein the degree to which the habit was ingrained, and how difficult it was to be conscious and override this habit, was frequently acknowledged. These sentiments were consistent with research outside of the sport communication domain that has found unintentional and periodic use of social media (e.g., Ahmed & Zia, 2022), particularly among experienced social media users (Lee & Ma, 2012). Given habitual media consumption includes a range of media usage levels (Diddi & LaRose, 2006), it is unsurprising that across demographic characteristics, platform preferences, usage levels, and fandom levels, participants consistently periodically checked their social media, often in a habitual manner.
Distinctly
Participants used a myriad of social media platforms, including Facebook, Instagram, LinkedIn, Pinterest, Reddit, Snapchat, Twitter, TikTok, and WhatsApp. This was consistent with past literature finding sport consumers used various social media platforms (Billings et al., 2017). However, more than half of the participants had the majority of their social media time highly concentrated on a single platform, wherein that platform was their dominant social media choice regardless of situation (e.g., physical surroundings, social surroundings, temporal perspective, task definition, and antecedent states; Belk, 1975). For example, Ben preferred Twitter, stating “I’m always just going to Twitter,” whereas Mia said, “good mood, bad mood, Instagram.” If participants had a preferred social media platform, that would be their go-to even if they acknowledged that another platform might be better suited to their needs. Dixie said, “If I Google a question about like anything in general, the number one page I find comes up for answers right away is always Twitter and I always think to myself, ‘Man, I should get Twitter’.” Despite understanding the value of Twitter as an information source, Dixie still did not adopt it.
Platform preferences became ingrained in participants over time, whereby participants did not want to adopt a new platform even if it would better fulfill their needs. This is consistent with scholarship that has found continued media use results in learned habits that in turn drive usage rather than intentional processing of rational factors or a deliberate cost–benefit analysis (Hu et al., 2018, 2021; Limayem et al., 2007). Moreover, it relates to the prior themes identified. Once habits developed with respect to social media usage, there was consistent usage of certain platforms, such as having Twitter open at work. Additionally, given participants consistently underscored an ease and lack of active involvement with respect to their social media usage (see passively theme), adopting a new platform or switching platforms was often seen as too much effort. Rather, participants were content passively scrolling along during breaks or relaxation times instead of actively seeking the optimal platform for any given experience.
For participants whose usage of social media platforms were more balanced, each platform was distinct. Olivia said, “I like the idea of having separate platforms where I do all those separate things,” and Riley acknowledged that “everything has its own time and place.” Eleanor was able to describe distinct usages of each platform conditional upon its content. The use of different platforms was not driven by platform features such as ephemeral content, but rather by the platforms’ content. Dillion and Watson agreed that decisions were content driven rather than based on platform features, while Jaxton stated, “content would drive you to the [platforms], not how I can engage with them.” This distinct content was largely a consequence of the different followings on each account. For example, Jaxton had “relatively distinct following feed lists” resulting in his platforms being “very different newsfeeds. When I’m reading one of them, I’m getting very different information on each platform. There is some crossover but not a ton. That helps drive why I would spend time on one versus the other.” Avery echoed this sentiment, acknowledging different information on different platforms because of the content. Given the standardization of platform designs and experiences (Pardes, 2020; Tolcheva, 2022), it is understandable that following (and, therefore, content) was the differentiating factor between platforms across participants.
It is worth noting that participants who actively used multiple different platforms tended to be older and established in their careers. Older participants noted that the following list on a given platform was reflective of their life at the time of the platforms’ release. For instance, Kylo noted Facebook was reserved for childhood friends and family, with Instagram being more reflective of their current friends and interests and LinkedIn being strictly professional given their career stage. Younger participants who favored a single platform often had all their friends on that platform rather than scattered across platforms.
Facebook, 2% sport, very, very little. Facebook is for families. Instagram, negative percent. That’s really just for looking at pictures, quick hits. It’s really Twitter and LinkedIn for sport, but two totally different uses.
This was inconsistent with past literature stating sport fans used multiple platforms for sport such as Pinterest and Snapchat (Billings et al., 2017); instead, if these platforms were used, they were for personal usage, and sport content was limited primarily to Instagram, Twitter, and Reddit.
Universally
The final theme captured the universal nature of social media behavior. In particular, sport content was a portion of the content being viewed and interacted with and social media accounts and platforms were used in consistent manners. When discussing the unique nature of sport content, Layla stated, “for me, [sport content is] in addition to everything—I think it’s one part of all the stuff that I look at” and with respect to social media usage Watson said, “that goes beyond sports itself.” Overall, regardless of fandom level or favorite sport, participants consistently indicated that sport content was just one aspect of their social media experience. As such, the motivations for using social media transcended content type. This was captured in the overarching purpose behind social media usage: information gathering. With respect to information gathering, Dillion said “both in general and sport. I go on there for the sports business news, NFL [National Football League] news, all of that, but as well as political and current events.” Likewise, Lucas said, “it’s more keeping up with news. News, in general, doesn’t matter if it’s sports news, general news.” and Sally said, “I use social media for a lot and to stay informed on different things, whether it’s what’s going on in the world, or what’s going on in sports, or what’s going on in music.”
I like accounts with varied content on similar topics. Sports accounts that maybe touch on music and media, and players as well as giving those updates, and interesting facts and stats, or something that’s more of a well-rounded follow, instead of just posting the same formatted images with daily score updates.
As captured throughout the literature review, there is a consistency across scholarship considering social media usage broadly and for sport content specifically. For instance, there has often been a large degree of overlap between motivations for using social media generally (e.g., Whiting & Williams, 2013), such as social interaction, passing time, information seeking, and opinion expression, and for using sport-specific social media (e.g., Filo et al., 2015), such as interactivity, information gathering, fandom, and entertainment. Furthermore, social media design and experiences are consistent across content types (e.g., whether it is a tweet about politics, the weather, or sports, you can like, retweet, or comment on it). Participants frequently consume sport and non-sport-related content simultaneously, such as using social media for game-related and game-unrelated activities while watching a live game on TV (Lewis et al., 2021). Finally, since participants did not feel that fandom was a significant driver for social media usage (see Further Probing section), particularly given how passive usage tended to be, fandom levels did not impact the findings.
A platform was opened to consume all new, relevant content in a general news feed, not to scroll through content on a specific account. Sally said, “I don’t just go on Instagram like, ‘Oh let me search LeBron James’ page’,” but rather to capture many perspectives on one topic. This was captured by Lucas’ statement, “I’m not just reading one person’s thing; I’m reading five people’s things about this one thing, this one topic.” Jimmy further elaborated on this point, saying “I wouldn’t necessarily go on somebody’s profile on Instagram or Twitter, because once you’ve got that piece of information, you’ll just move on from it.” Rather than consuming a single account’s content, social media was valuable to participants as it was able to synthesize and present different snippets of information on a single topic. As such, different types of contents, such as sport versus general news, did not impact the findings nor did the degree to which sport content was a component of their social media feed. Instead, the findings suggest a consistent, habitual, and universal approach to passive social media use across demographic characteristics, social media usage levels and platform preferences, and fandom levels. Given the sport focus of our research question, we conducted further probing throughout the interviews to try to tease out any missed nuances.
Further Probing
The content’s still there and it’s not much higher or much lower in quantity or in interest for me. I don’t think that there not being sports and basically any sport taking place really changes how I’m using social media or how I’m using social media for sports consumption.
Moreover, as aforementioned, participants’ level of fandom did not introduce or result in different social media patterns or behaviors. This finding made sense given that participants viewed sport content as just another form of content within the social media platform (see the distinctly theme). Even when explicitly asked about it, fandom was not a motivation that participants resonated with. Lucas said, “that to me is more the in-person expression as opposed to through a digital media.” Likewise, Sally said, “I am a huge fan of the Eagles and the Sixers, but I do not tweet or post a lot at all about my opinion,” Dillion said, “my love of the Eagles isn’t driving me to social media to interact with all of their content,” and Jaxton said, “I occasionally will engage with material that other people post and leave a few comments but it’s not driving a lot of my behavior.” Although participants identified as fans and had feelings of fandom, it did not lead to different or unique social media activity. This was supported by Watson who said, “I definitely resonate with the feeling, but I don’t publish the feeling or rarely will I publish the feeling on Instagram publicly.” Given that fandom, or expression of fandom, was not driving social media usage, it is unsurprising that the themes found did not differ across fandom levels. Given the consistent usage experience (i.e., standardization of platforms) and motivations driving usage (e.g., information gathering), it is understandable that despite significant further probing, additional nuances could not be identified with respect to the novelty or uniqueness of sport content. However, the lack of depth with respect to how social media is used in and of itself is an important finding.
Discussion and Implications
Three important implications can be derived from the five themes identified in this study. First, participants often used social media out of habit, even going as far as to say that it has become habitual behavior. This lends credence to the criticism that U&G theory overstates the purposefulness of consumers (White, 1994) and to competing research suggesting that media consumption is predominantly automatic in nature, with behavioral tendencies or habits emerging overtime that override rational and deliberate media evaluation and selection (Hofmann et al., 2009; Hu et al., 2018, 2021). For instance, participants developed platform preferences and even if they acknowledged that another platform might better suit their needs in a given situation, their platform preferences overruled the willingness to adopt or use a different platform. This, in turn, provides evidence that continued social media usage was not driven by conscious evaluations of media (e.g., cost–benefit analysis and identification of unfulfilled needs), but rather once a habit is formed, the habit is the only driving factor that matters (Hu et al., 2021). The only factor that participants consistently acknowledged as influencing the formation of these habits was time, suggesting that they learned these behaviors or developed these routines over time. This aligns with scholarship in the general context finding more experienced users may rely on routines and habits with respect to social media behaviors (Lee & Ma, 2012). Given that social media platforms are intentionally designed to be addictive (Schwär, 2021; Weller, 2018) and that it is difficult to pinpoint how different mechanisms individually impact prolonged usage time (Montag et al., 2019), it is unsurprising that it was difficult for participants to identify what has led to habit formation.
Such habitual, routine, and/or unconscious behavior directly contradicts U&G theory’s perspective that users will select the media that best satisfies their needs and only continue media use so long as their needs are satisfied (Katz et al., 1973). This challenges the dominance of the U&G perspective in sport communication scholarship that has frequently sought to identify motivations of social media use. It also identifies a potential bias in existing scholarship, namely, that it overstates or implies a more active, conscious involvement of social media users. This calls for our scholarship to consider the habitual nature of (at least some) social media use that has been identified in general communication scholarship (e.g., Diddi & LaRose, 2006; LaRose et al., 2003). This finding does not discredit U&G theory or the valuable insight obtained by focusing on motivations driving social media use, but rather, acknowledges that while some media use may be purposeful and goal directed, there is also a portion that is habitual in nature. It also highlights that while U&G theory may aptly capture media adoption, repeated media use results in the formation of habit (and the strength of that habit; Diddi & LaRose, 2006; Lee & Ma, 2012) and, thus, should be considered given the length of time social media has been used by the sport industry. Consequently, our scholarship should be aware of this range of media behaviors throughout its investigations.
Second, the theme of “passively” highlights the lack of engagement with (e.g., commenting on posts and interacting with strangers) and (co-)creation of content. This contradicts research that suggests social media is a unique medium sport fans use to generate content and interact with sport entities (e.g., Pegoraro, 2010), which has been a dominate narrative in sport social media research. For example, prior scholarship has focused on the identification of motivations driving sport social media usage, often identifying interaction as a key motive (Abeza et al., 2015; Filo et al., 2015). This focus may overstate the amount of interaction that is occurring or misattribute it to general interaction rather than the friend/family-specific interactions through private channels found in this study. Moreover, recent scholarship has investigated factors that drive engagement with sport social media accounts (e.g., Kennedy et al., 2021). While valuable to understand what drives social media engagement (e.g., liking or commenting), this likely only captures behaviors of a select subset of social media users. Given the consistency of passive usage across participants regardless of demographic characteristics, fandom levels, and/or social media usage patterns, such a subset is not likely reflective of the average social media user. Similarly, content analyses, a popular methodology in social media scholarship (Abeza et al., 2015), while able to provide valuable insight, focus again on a select subset of active users.
Identifying that at least some social media use is habitual and passive in nature suggests that scholarship considering engagement or fan-generated conversations only captures a subset of social media users. That is not to say that it is not valuable, particularly given that passive users will likely be exposed to popular content, but rather to acknowledge that such examinations are not always representative of all social media users. Theoretically, identifying that social media usage exists on a continuum from habitual and passive to purposeful and active can help to inform scholarship going forward as well as acknowledge delimitations of scholarship focusing on engagement or fan-generated posts. Managerially, this research suggests that sport entities should expect lower levels of engagement among users, and advertisers should incorporate measures other than engagement to evaluate content and strategy.
Finally, an overarching trend of consistency emerged based on consumers’ learned behavioral patterns and habits. For instance, in the theme of distinctly, participants outlined how they would continue to use a social media platform, even if they knew a superior one was available to them. Rather, based on their ingrained preferences, consumers would often default to a given platform regardless of the situation. Moreover, in the theme of universally, participants outlined how they would use social media in the same ways regardless of content type or platform. For example, participants outlined how they would engage in the same behaviors for all content types, such as looking up a sport score or an athlete just as they would look up news updates or a celebrity. This notion is exemplified within existing scholarship, such as consistent driving motives identified within sport communication studies (e.g., motive of information gathering captured by Billings et al. [2019], Billings et al. [2017], Frederick et al. [2012], Gibbs et al. [2014], Lewis et al. [2017], Ruihley and Hardin [2011], and Witkemper et al. [2012]) and general social media studies (e.g., Whiting & Williams, 2013).
The trend of consistency was further captured in the dominance of the themes across participants. Though some exceptions were previously noted (e.g., older respondents tended to have more platforms used distinctly), by and large, there was a lack of nuance in the themes or findings across demographic characteristics, fandom levels, and social media patterns. Given social media platforms are relatively standardized with respect to experiences (Pardes, 2020; Tolcheva, 2022) and there are relatively consistent motivations for usage (e.g., information gathering and diversion), it is understandable that social media usage has evolved to be homogenous among users. Such consistency has theoretical and managerial implications.
This consistency to social media usage allows for generalizability of theoretical insights within sport communication and across other academic disciplines. It also supports emerging scholarship that has found habits emerge with continued social media use that, in turn, drive and sustain behavior (e.g., Hu et al., 2018, 2021). Theoretically, a consistency in social media usage improves the generalizability of sport communication scholarship across (sport) contexts while allowing for future studies to leverage knowledge accrued from various disciplines, such as general communication literature. However, it also raises important questions that our discipline should seek to address around the novelty or uniqueness of the sport context. In particular, the results consistently found that participants viewed sport content as just one type of many content areas or interests they followed on social media. Moreover, fandom consistently failed to influence the themes or provide nuance among the findings. Hence, the specificity of this research question around sport content and consumers may have unnecessarily narrowly defined the scope of the research. For example, participants indicated that they would follow an athlete for the same reasons they would a musician or celebrity, or look for updates about a sport the same way they would about politics or local news. In turn, sport communication scholars should seek to identify whether industry-specific nuances do exist for sport and/or focus on the role of sport communication scholarship within broader communication scholarship.
The overall trend of consistency also suggests the potential to move away from evaluating social media constructs and ideas across various contexts (e.g., motivations for following specific athletes vs. specific teams vs. specific leagues), rather generalizing across specific sport contexts. Managerially, sport organizations could then look to other types of organizations for guidance with respect to best practices for social media strategies and measurement, increasing the insights available to them. Since sport content is a component of social media content for consumers, sport organizations can embrace variety in their content and posting strategies (e.g., not just feature score updates but include other types of content, like player check-ins). Effectively, by examining how sport consumers use social media, this scholarship identified three potential biases in existing sport communication scholarship, which can inform scholarship moving forward: (a) an overstatement of how active and purposeful consumers are in their social media usage, (b) an overcomplication of social media usage across factors, and (c) an overstatement of the uniqueness of the sport context.
Limitations and Future Directions
There are limitations to this research that should be acknowledged to inform future research. A qualitative design allowed for an in-depth exploration into how consumers use sport social media, consistent with the overarching research purpose (see Methods section for additional details and further justification of the research approach). Particular attention was paid to gathering a diverse sample that would be informative with respect to the research question, including recruiting participants of varying backgrounds and with various favorite sports, fandom levels, and social media usage levels. Between our rigorous methodology and the consistency of our results with communication scholarship on habitual social media use, we are confident in our findings. Yet, this research was derived from a homogenous population with respect to why they used social media (e.g., information gathering) and their social media experiences (e.g., standardization of platforms). It focused on a specific subset of social media users, namely, Canadian and American adults who worked full time and were neither professional nor amateur content creators. While the purpose of qualitative research is not to generalize (Carminati, 2018; Polit & Beck, 2010), rather to provide “a rich contextualized understanding of some aspect of human experience” (Polit & Beck, 2010, p. 1451), and “a small sample size may be more useful in examining a situation in depth from various perspectives,” (Myers, 2000, p. 3), it is still worth acknowledging the limitations with the sample and/or research methodology. By providing a rich, in-depth background of the qualitative sample, transferability judgments can be made by others (since the onus of providing an index of transferability does not fall on the researchers; Guba & Lincoln, 1985). Still, it is important to acknowledge the delimitations associated with the sample, qualitative interview methodology, and even the research goals of this study as well as the resulting limitations of these research design decisions. Doing so helps identify future research goals to further this line of inquiry that were beyond the scope of this exploration into the complexities and nuances of how sport consumers use sport social media. For example, future research with a goal of generalizability could confirm our findings to ensure results are not reflective of an idiosyncratic sample and consider populations beyond the scope of our study using quantitative methodologies. Future research could also focus on populations with different motivations or usage experiences (e.g., content creators) to see if different themes arise.
This research found that for sport consumers, social media can range from habitual to purposeful in nature. Interviews suggested that media usage was habitual and periodic throughout the day, but purposeful in the evenings when sought to complement evening entertainment. Findings also suggested that platform and social media tenure were a factor in habit development. Future research can seek to identify patterns within usage behaviors (i.e., purposeful vs. unconscious) to help inform application development and social media marketing and communication strategies. Future research can explore how the type of social media use (e.g., habitual through to nonhabitual) impacts important behaviors and outcome metrics such as purchases and repeat consumption.
This research found evidence that social media preferences developed overtime, leading to platform selection and usage occurring out of habit, rather than as an evaluation of which platform would best serve the user. Many users indicated their social media use was centralized to a favorite platform, with those who used multiple platforms indicating selection was based on following lists rather than platform characteristics. Future scholarship should confirm these patterns, such as how behavioral usage of media may change over time. It should also begin to consistently acknowledge habit as a driver of media use, while considering the reality of social media in consumers’ lives (i.e., a part of their daily routine rather than actively sought after).
Conclusions
In conclusion, to extend existing sport communication scholarship, this research considered how sport social media is used. Interview participants indicated that a substantial amount of their social media use was habitual in nature, based off habits or learned preferences. Consumers often used social media in a passive manner, with limited intention to generate new content or interact with content (e.g., comment on strangers’ posts) suggesting that social media may have evolved into a broadcast medium, with consumers consuming but not creating content. As such, we encourage scholars to at least consider that not all social media usage will be active, purposeful, and/or goal directed in nature. Overall, these results enhance our understanding of the role social media has evolved to hold in sport fans’ lives.
Notes
A number of criticisms of U&G theory have emerged since its introduction including (a) the nature of the theory forcing it to be individualistic, limiting generalizability of findings, with studies being too compartmentalized and failing to synthesize results; (b) motivations being more dependent on researchers’ input than that of the participants; (c) a lack of clarity and precision among central concepts; and (d) overstating the purposeful nature of audience members (Elliott, 1974; Ruggiero, 2000; White, 1994). Though important to acknowledge all these criticisms, our review focuses on the fourth and final criticism to ensure a clear and concise narrative.
When there were little or no relevant new codes found in the data, with codes repeating without further contribution or understanding, saturation was reached (Hennink & Kaiser, 2022). When there is a homogenous population, saturation can be achieved within a narrow range (i.e., 9–17 interviews; Hennink & Kaiser, 2022). While our sample was heterogenous with respect to demographics, geographic region (within United States and Canada), and fandom levels, it proved homogenous with respect to how and why social media was used. For instance, true to prior scholarship findings on consistent motivations for using social media (Filo et al., 2015), our study consistently found that social media, regardless of platform, was used for information gathering and diversion (see Universally theme). Similarly, even when asked about Belk’s (1975) situational variables (e.g., physical surroundings, social surroundings, temporal perspective, task definition, and antecedent states), participants consistently indicated that their platform preferences and usage did not change (see Distinctly theme). Moreover, there is significant homogeneity across social media platforms, with significant copycatting between platforms in attempts to increase engagement resulting in standardized experiences across platforms (Pardes, 2020; Tolcheva, 2022). Interview participants echoed this similarity between platforms when they indicated that who they followed, rather than platform features, differentiated the platforms (see Distinctly theme). Effectively, when the platforms themselves are increasingly similar and users’ motivations for using platforms are consistent, the net result is a homogenous sample with respect to the focus of the study. As such, achieving saturation within 15 interviews and confirming that saturation across seven additional interviews, aligns with expectations based on standards for theoretical saturation and prior scholarship (e.g., 15 interviews of female fans to represent female fans ranging from 24 to 60 years old with a variety of fandom levels across the United Kingdom, Europe, and North America; Fenton et al., 2021).
References
Abeza, G., O’Reilly, N., Séguin, B., & Nzindukiyimana, O. (2015). Social media scholarship in sport management research: A critical review. Journal of Sport Management, 29(6), 601–618. https://doi.org/10.1123/JSM.2014-0296
Abeza, G., & Sanderson, J. (2022). Theory and social media in sport studies. International Journal of Sport Communication, 15(4), 284–292. https://doi.org/10.1123/ijsc.2022-0108
Ahmed, S., & Zia, A. (2022). Uses and gratifications theory and social media interactivituy: A demographic study in Lahore, Pakistan. Global Regional Review, 7(1), 50–60. https://doi.org/10.31703/grr.2022(VII-I).06
Barriball, K.L., & While, A. (1994). Collecting data using a semi-structured interview: A discussion paper. Journal of Advanced Nursing, 19(2), 328–335. https://doi.org/10.1111/j.1365-2648.1994.tb01088.x
Belk, R.W. (1975). Situational variables and consumer behavior. Journal of Consumer Research, 2(3), Article 157. https://doi.org/10.1086/208627
Billings, A.C., Broussard, R.M., Xu, Q., & Xu, M. (2019). Untangling international sport social media use: Contrasting U.S. and Chinese uses and gratifications across four platforms. Communication & Sport, 7(5), 630–652. https://doi.org/10.1177/2167479518790014
Billings, A.C., Qiao, F., Conlin, L., & Nie, T. (2017). Permanently desiring the temporary? Snapchat, social media, and the shifting motivations of sports fans. Communication & Sport, 5(1), 10–26. https://doi.org/10.1177/2167479515588760
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Carminati, L. (2018). Generalizability in qualitative research: A tale of two traditions. Qualitative Health Research, 28(13), 2094–2101. https://doi.org/10.1177/1049732318788379
Chiu, C.-M., & Huang, H.-Y. (2015). Examining the antecedents of user gratification and its effects on individuals’ social network services usage: The moderating role of habit. European Journal of Information Systems, 24(4), 411–430. https://doi.org/10.1057/ejis.2014.9
Clavio, G., & Frederick, E. (2014). An exploration of motivations for social sharing and locational social media usage among sport fans. Journal of Applied Sport Management, 6(2), 70–85.
Clavio, G., & Kian, T.M. (2010). Uses and gratifications of a retired female athlete’s Twitter followers. International Journal of Sport Communication, 3(4), 485–500. https://doi.org/10.1123/ijsc.3.4.485
Clavio, G., & Walsh, P. (2014). Dimensions of social media utilization among college sport fans. Communication & Sport, 2(3), 261–281. https://doi.org/10.1177/2167479513480355
Collins, D.R., Heere, B., Shapiro, S., Ridinger, L., & Wear, H. (2016). The displaced fan: The importance of new media and community identification for maintaining team identity with your hometown team. European Sport Management Quarterly, 16(5), 655–674. https://doi.org/10.1080/16184742.2016.1200643
Creswell, J.W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage.
Denzin, N.K., & Lincoln, Y.S. (2011). The SAGE handbook of qualitative research (4th ed.). SAGE Publications, Inc.
Diddi, A., & LaRose, R. (2006). Getting hooked on news: Uses and gratifications and the formation of news habits among college students in an internet environment. Journal of Broadcasting & Electronic Media, 50(2), 193–210. https://doi.org/10.1207/s15506878jobem5002_2
Du, J., Kerkhof, P., & van Koningsbruggen, G.M. (2019). Predictors of social media self-control failure: Immediate gratifications, habitual checking, ubiquity, and notifications. Cyberpsychology, Behavior, and Social Networking, 22(7), 477–485. https://doi.org/10.1089/cyber.2018.0730
Elliott, P. (1974). Uses and gratifications research: A critique and a sociological alternative. In J.G. Blumer & E. Katz (Eds.), The uses of mass communications: Current perspectives on gratifications research (pp. 249–268). Sage.
Fenton, A., Gillooly, L., & Vasilica, C.M. (2021). Female fans and social media: Micro-communities and the formation of social capital. European Sport Management Quarterly. Advance online publication. https://doi.org/10.1080/16184742.2020.1868546
Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport Management Review, 18(2), 166–181. https://doi.org/10.1016/j.smr.2014.11.001
Fleiss, L., Levin, B., & Paik, M.C. (2003). The measurement of interrater agreement. In A.W. Shewart & S.S. Wilks (Eds.), Statistical methods for rates and proportions (3rd ed., pp. 598–626). John Wiley & Sons.
Frederick, E.L., Lim, C.H., Clavio, G., & Walsh, P. (2012). Why we follow: An examination of parasocial interaction and fan motivations for following athlete archetypes on Twitter. International Journal of Sport Communication, 5(4), 481–502. https://doi.org/10.1123/ijsc.5.4.481
Giannakos, M.N., Chorianopoulos, K., Giotopoulos, K., & Vlamos, P. (2013). Using Facebook out of habit. Behaviour & Information Technology, 32(6), 594–602. https://doi.org/10.1080/0144929X.2012.659218
Gibbs, C., O’Reilly, N., & Brunette, M. (2014). Professional team sport and Twitter: Gratifications sought and obtained by followers. International Journal of Sport Communication, 7(2), 188–213. https://doi.org/10.1123/IJSC.2014-0005
Gibbs, G.R. (2007). Analyzing qualitative data. Sage. https://doi.org/10.4135/9781849208574
Grellhesl, M., & Punyanunt-Carter, N.M. (2012). Using the Uses and Gratifications Theory to understand gratifications sought through text messaging practices of male and female undergraduate students. Computers in Human Behavior, 28(6), 2175–2181. https://doi.org/10.1016/j.chb.2012.06.024
Griffiths, M.D. (2018). Adolescent social networking: How do social media operators facilitate habitual use? Education and Health, 36(3), 66–69.
Griffiths, M.D., & Kuss, D. (2019). The rise—and rise—of problematic social media use. Psychology Today. https://www.psychologytoday.com/blog/in-excess/201901/the-rise-and-rise-problematic-social-media-use
Guba, E.G. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries. Education Communication and Technology Journal, 29(2), 75–91. https://doi.org/10.1007/BF02766777
Guba, E.G., & Lincoln, Y.S. (1985). Naturalistic inquiry. Sage Publications.
Hambrick, M.E., & Svensson, P.G. (2015). Gainline Africa: A case study of sport-for-development organizations and the role of organizational relationship building via social media. International Journal of Sport Communication, 8(2), 233–254. https://doi.org/10.1123/ijsc.2014-0087
Hanna, P. (2012). Using internet technologies (such as Skype) as a research medium: A research note. Qualitative Research, 12(2), 239–242. https://doi.org/10.1177/1468794111426607
Hennink, M., & Kaiser, B.N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292, Article 114523. https://doi.org/10.1016/j.socscimed.2021.114523
Hofmann, W., Friese, M., & Strack, F. (2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162–176. https://doi.org/10.1111/j.1745-6924.2009.01116.x
Hu, T., Luo, X., Dai, H., & Zhang, X. (2021). Developing a value assessment framework of habitual social media use: A grounded theory approach. Journal of Electronic Commerce Research, 22(2), 128–154.
Hu, T., Stafford, T.F., Kettinger, W.J., Zhang, X., & Dai, H. (2018). Formation and effect of social media usage habit. Journal of Computer Information Systems, 58(4), 334–343. https://doi.org/10.1080/08874417.2016.1261378
Irwin, M.L. (2017). The dynamics of media use, attention, and behavioral control. The Ohio State University.
Jensen, P.S., Mrazek, D., Knapp, P.K., Steinberg, L., Pfeffer, C., Schowalter, J., & Shapiro, T. (1997). Evolution and revolution in child psychiatry: ADHD as a disorder of adaptation. Journal of the American Academy of Child & Adolescent Psychiatry, 36(12), 1672–1681. https://doi.org/10.1097/00004583-199712000-00015
Kassing, J.W., & Sanderson, J. (2010). Fan–athlete interaction and Twitter tweeting through the Giro: A case study. International Journal of Sport Communication, 3(1), 113–128. https://doi.org/10.1123/ijsc.3.1.113
Katz, E. (1959). Mass communications research and the study of popular culture: An editorial note on a possible future for this journal. Studies in Public Communication, 2, 1–6. https://repository.upenn.edu/asc_papers/165
Katz, E., Blumler, J.G., & Gurevitch, M. (1973). Uses and gratifications research. The Public Opinion Quarterly, 37(4), 509–523. https://doi.org/10.1086/268109
Kemmis, S. (1980). The imagination of the case and the invention of the study. In H. Simons (Ed.), Towards a science of the singular: Essays about case study in education research and evaluation (pp. 93–142). University of East Anglia: Centre for Applied Research in Education.
Kennedy, H., Kunkel, T., & Funk, D.C. (2021). Using predictive analytics to measure effectiveness of social media engagement: A digital measurement perspective. Sport Marketing Quarterly, 30(4), 265–277. https://doi.org/10.32731/SMQ.304.1221.02
Kim, H.S., & Kim, M. (2020). Viewing sports online together? Psychological consequences on social live streaming service usage. Sport Management Review, 23(5), 869–882. https://doi.org/10.1016/j.smr.2019.12.007
Knafl, K.A., & Breitmayer, B.J. (1989). Triangulation in qualitative research: Issues of conceptual clarity and purpose. In J.M. Morse (Eds.), Qualitative nursing research as contemporary dialogue. Sage Publications.
Krefting, L. (1991). Rigor in qualitative research: The assessment of trustworthiness. American Journal of Occupational Therapy, 45(3), 214–222. https://doi.org/10.5014/ajot.45.3.214
Kvale, S., & Brinkmann, S. (2009). Interviews: Learning the craft of qualitative research interviewing. Sage.
Larkin, B.A., & Fink, J.S. (2016). Fantasy sport, FoMO, and traditional fandom: How second-screen use of social media allows fans to accommodate multiple identities. Journal of Sport Management, 30(6), 643–655. https://doi.org/10.1123/jsm.2015-0344
LaRose, R. (2010). The problem of media habits. Communication Theory, 20(2), 194–222. https://doi.org/10.1111/j.1468-2885.2010.01360.x
LaRose, R., Lin, C.A., & Eastin, M.S. (2003). Unregulated internet usage: Addiction, habit, or deficient self-regulation? Media Psychology, 5(3), 225–253. https://doi.org/10.1207/S1532785XMEP0503_01
Lasswell, H.D. (1948). Communications research. Harper.
Lee, C.S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331–339. https://doi.org/10.1016/j.chb.2011.10.002
Leung, L., & Wei, R. (2000). More than just talk on the move: Uses and gratifications of the cellular phone. Journalism & Mass Communication Quarterly, 77(2), 308–320. https://doi.org/10.1177/107769900007700206
Lewis, M., Brown, K.A., & Billings, A.C. (2017). Social media becomes traditional: Sport media consumption and the blending of modern information pathways. Journal of Global Sport Management, 2(2), 111–127. https://doi.org/10.1080/24704067.2017.1314764
Lewis, N., Gantz, W., & Wenner, L.A. (2021). What we do when we watch live sports: An analysis of concurrent viewing behaviors. International Journal of Sport Communication, 14(2), 153–167. https://doi.org/10.1123/ijsc.2020-0270
Li, B., Dittmore, S.W., Scott, O.K.M., Lo, W., & Stokowski, S. (2019). Why we follow: Examining motivational differences in following sport organizations on Twitter and Weibo. Sport Management Review, 22(3), 335–347. https://doi.org/10.1016/j.smr.2018.04.006
Limayem, M., Hirt, S.G., & Cheung, C.M.K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705–737. https://doi.org/10.2307/25148817
McQuail, D., Blumer, J.G., & Brown, J.R. (1972). The television audience: A revised perspective. In D. McQuail (Ed.), Media studies: A reader (pp. 438–453). Sage Publications.
Montag, C., Lachmann, B., Herrlich, M., & Zweig, K. (2019). Addictive features of social media/messenger platforms and freemium games against the background of psychological and economic theories. International Journal of Environmental Research and Public Health, 16(14), Article 2612. https://doi.org/10.3390/ijerph16142612
Moore, J.H. (2018). Reading, watching, and tweeting about sports: An analysis of sport-news retention. International Journal of Sport Communication, 11(4), 503–528. https://doi.org/10.1123/ijsc.2018-0081
Myers, M. (2000). Qualitative research and the generalizability question: Standing firm with proteus. The Qualitative Report, 4(3), Article 2925. https://doi.org/10.46743/2160-3715/2000.2925
O’Hallarn, B., Shapiro, S.L., Hambrick, M.E., Wittkower, D.E., Ridinger, L., & Morehead, C.A. (2018). Sport, Twitter hashtags, and the public sphere: A qualitative test of the phenomenon through a Curt Schilling case study. Journal of Sport Management, 32(4), 389–400. https://doi.org/10.1123/jsm.2017-0230
Ortiz de Guinea, A., & Markus, M.L. (2009). Why break the habit of a lifetime? Rethinking the roles of intention, habit, and emotion in continuing information technology use. MIS Quarterly, 33(3), 433–444. https://doi.org/10.2307/20650303
Pardes, A. (2020). All the social media giants are becoming the same. Wired. https://www.wired.com/story/social-media-giants-look-the-same-tiktok-twitter-instagram/
Parry, D.A., Davidson, B.I., Sewall, C.J.R., Fisher, J.T., Mieczkowski, H., & Quintana, D.S. (2021). A systmatic review and meta-analysis of discrepancies between logged and self-reported digital media use. Nature Human Behaviour, 5(11), 1535–1547. https://doi.org/10.1038/s41562-021-01117-5
Pegoraro, A. (2010). Look who’s talking—Athletes on Twitter: A case study. International Journal of Sport Communication, 3(4), 501–514. https://doi.org/10.1123/ijsc.3.4.501
Polit, D.F., & Beck, C.T. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47(11), 1451–1458. https://doi.org/10.1016/j.ijnurstu.2010.06.004
Popp, B., & Woratschek, H. (2016). Introducing branded communities in sport for building strong brand relations in social media. Sport Management Review, 19(2), 183–197. https://doi.org/10.1016/j.smr.2015.06.001
Price, B.L., Farren, G.L., Stoll, J.A., Goldsmith, A., Carroll, M., & Martin, C. (2022). Tinkering with policies in the digital age: How interscholastic athletic directors address social media use by student-athletes. International Journal of Sport Communication, 15(1), 53–65. https://doi.org/10.1123/ijsc.2021-0092
Ruggiero, T.E. (2000). Uses and gratifications theory in the 21st century. Mass Communication and Society, 3(1), 3–37. https://doi.org/10.1207/S15327825MCS0301_02
Ruihley, B.J., & Hardin, R.L. (2011). Message boards and the fantasy sport experience. International Journal of Sport Communication, 4(2), 233–252. https://doi.org/10.1123/ijsc.4.2.233
Sanderson, J. (2013). From loving the hero to despising the villain: Sports fans, Facebook, and social identity threats. Mass Communication and Society, 16(4), 487–509. https://doi.org/10.1080/15205436.2012.730650
Schwär, H. (2021). How Instagram and Facebook are intentionally designed to mimic addictive painkillers. Business Insider. https://www.businessinsider.com/facebook-has-been-deliberately-designed-to-mimic-addictive-painkillers-2018-12
Singer, J.B. (1998). Online journalists: Foundations for research into their changing roles. Journal of Computer-Mediated Communication, 4(1), Article 88. https://doi.org/10.1111/j.1083-6101.1998.tb00088.x
Smith, B., & McGannon, K.R. (2018). Developing rigor in qualitative research: Problems and opportunities within sport and exercise psychology. International Review of Sport and Exercise Psychology, 11(1), 101–121. https://doi.org/10.1080/1750984X.2017.1317357
Stafford, T.F., Stafford, M.R., & Schkade, L.L. (2004). Determining uses and gratifications for the Internet. Decision Sciences, 35(2), 259–288. https://doi.org/10.1111/j.00117315.2004.02524.x
Tang, T., Schallhorn, C., Guo, Q., & Coombs, D.S. (2022). The world is watching women’s soccer: Audiences’ multiplatform experience during the world cup. International Journal of Sport Communication, 15(2), 127–138. https://doi.org/10.1123/ijsc.2021-0121
Tolcheva, S. (2022). Are all social media platforms becoming the same? MUO. https://www.makeuseof.com/social-media-sites-becoming-the-same/
Turner, D.W., & Hagstrom-Schmidt, N. (2022). Appendix: Qualitative interview design. In M. McKinney, K. Pattison, S. LeMire, K. Anders, & N. Hagstrom-Schmidt (Eds.), Howdy or Hello? Technical and professional communication (2nd ed.). Press Books.
Uhrich, S. (2014). Exploring customer-to-customer value co-creation platforms and practices in team sports. European Sport Management Quarterly, 14(1), 25–49. https://doi.org/10.1080/16184742.2013.865248
Vishwanath, A. (2015). Habitual Facebook use and its impact on getting deceived on social media. Journal of Computer‐Mediated Communication, 20(1), 83–98. https://doi.org/10.1111/jcc4.12100
Wakefield, K. (2016). Using fan passion to predict attendance, media consumption, and social media behaviors. Journal of Sport Management, 30(3), 229–247. https://doi.org/10.1123/jsm.2015-0039
Walker, M., Hodge, C., & Bennett, G. (2017). The freeloader effect: Examining the influence of engagement and attitudes in a virtual fan community. Sport Marketing Quarterly, 26(3), 130–139.
Weiner, J., & Dwyer, B. (2017). A new player in the game: Examining differences in motives and consumption between traditional, hybrid, and daily fantasy sport users. Sport Marketing Quarterly, 26(3), 140–152.
Weller, C. (2018). A group of former Facebook and Apple employees are teaming up to warn kids about tech addiction. Business Insider. https://www.businessinsider.com/ex-facebook-and-google-employees-launch-anti-tech-addiction-campaign-2018-2
White, R.A. (1994). Audience interpretation of media: Emerging perspectives. Communication Research Trends, 14(3), 3–36.
Whiting, A., & Williams, D. (2013). Why people use social media: A uses and gratifications approach. Qualitative Market Research: An International Journal, 16(4), 362–369. https://doi.org/10.1108/QMR-06-2013-0041
Witkemper, C., Lim, C.H., & Waldburger, A. (2012). Social media and sports marketing: Examining the motivations and constraints of Twitter users. Sport Marketing Quarterly, 21(3), 170–183.
Wood, W., Quinn, J.M., & Kashy, D.A. (2002). Habits in everyday life: Thought, emotion, and action. Journal of Personality and Social Psychology, 83(6), 1281–1297. https://doi.org/10.1037/0022-3514.83.6.1281
Wu, J.-H., Wang, S.-C., & Tsai, H.-H. (2010). Falling in love with online games: The uses and gratifications perspective. Computers in Human Behavior, 26(6), 1862–1871. https://doi.org/10.1016/j.chb.2010.07.033
Zeren, D., Erkan, I., & Acikgoz, F. (2022). Sport marketing and social media strategies: A literature review and research agenda. Sport marketing in a global environment (1st ed.). Routledge.
