Social Media and Sport Research: Empirical Examinations Showcasing Diversity in Methods and Topics

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Jimmy Sanderson Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, TX, USA

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Gashaw Abeza Department of Kinesiology, Towson University, Towson, MD, USA

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This commentary introduces the second of two special issues in the International Journal of Sport Communication centered on social media and sport. The empirical studies presented in this issue illustrate both the diversity of topics and methodological approaches utilized by researchers working at the intersection of social media and sport. Research articles in this issue analyze topics ranging from sport consumer behavior to online fan communities to coaches’ perceptions of activism-related content posted on team social media accounts. The research presented here also employs a variety of methodological approaches including experimental design, critical discourse analysis, rhetorical analysis, and applications of artificial intelligence and machine learning. Collectively, these studies offer a foundation on which future research in social media and sport can build to continue to enhance our understanding of social media’s impact on the sport world.

Welcome to the second of two special issues on social media and sport in the International Journal of Sport Communication (IJSC). In the first volume, IJSC 16(3), September 2023, scholars provided commentaries on various research streams within social media and sport. These commentaries helped to evaluate the current state of the sport and social media literature, while also identifying future directions for researchers to traverse. Following that first volume of scholarly commentaries, this issue consists of empirical research into various content areas of social media and sport. Social media and sport research has grown significantly over the past decade. As inquiry in this area has increased, researchers have examined a number of directions and topical areas. This includes, but is not limited to, marketing, public relations, fan behavior, consumer behavior, athlete branding, and organizational governance. We believe that the current grouping of research articles reflects the diversity of topics and methodological approaches within the social media and sport literature. Additionally, several of the articles in this issue highlight the role of emerging technology such as machine learning and artificial intelligence and how these tools can be used to enhance and strengthen social media and sport research.

Achen et al. (2024) engage in an analysis of social media messages and its influence on consumer engagement. Their results indicate that participants were more likely to comment on platforms such as Facebook and Twitter and were more likely to purchase after seeing Twitter content. They also found that certain kinds of messages from the sport organization, such as informational and relationship building posts, were more likely to induce fans to comment, like, and share content, while sales-themed posts were more likely to lead to purchases. Their research illustrates the value of using experimental design in social media research, while also demonstrating how sport organizations can tailor social media content in specific ways to reach organizational goals on platforms such as Twitter, such as increasing engagement by employing invitational and relational strategies.

Popp et al. (2024) offer an investigation of artificial intelligence to examine sentiments from Twitter users and explore how they may be related to ticket sales. Among others, their results demonstrated relationships between sentiment scores and season ticket sales. They also found that frequency of content posted on Twitter had a significant influence on ticket sales. Their research demonstrates how sport organizations can affect the narrative of conversations through the type of social media messaging they construct. Their research also illustrates the value that artificial intelligence possesses for social media and sport research, particularly in working with and mining from large data sets.

Bunch et al. (2024) provide an analysis of intercollegiate coaches and their perceptions of how their athletic department used social media for activism-related initiatives. They found that coaches supported activism expressed via social media, while being less confident about content related to racial justice on team accounts. The authors noted how the content posted on social media can influence a coach’s ability to recruit, change culture, and impact the larger community. They further observed gender differences, including female coaches being less upset with racial justice posts than male coaches. Their research highlights the impact that social media content can have on the leadership and organization of a sports team. Their study provides a foundational springboard for compelling future work in sport, social media, and activism.

Greenhalgh and Goebert (2024) offer an analysis of NASCAR’s use of iRacing to bolster fan recruitment, including capturing new and more diverse fan markets. Through an investigation on Twitter, their research illustrates how the shift from traditional racing to iRacing did assist NASCAR in obtaining these objectives. Their findings highlight how sport organizations can benefit from emerging technology and how it can help them grow their fan base. Their research also illustrates compelling future directions for both sport organizations and athletes to consider, including athletes potentially being required to engage in virtual sport as part of their job. Their work also offers a baseline for future work to investigate immersive sport experiences and how technology may shift traditional fan consumption experiences.

Cao et al. (2024) investigate online fan communities and consumer engagement behavior centered on the Chinese Super League on Weibo. Their findings illustrate how consumer engagement behavior can manifest negatively, but they argue that such negative valence can actually help sport organizations improve. Their research further indicates that fans displaying negative consumer engagement behavior are highly identified and have a profound sense of belonging to the team. Given their results, the authors argue that sport organizations should prioritize building strong, vibrant, online communities, while also working to enhance fans’ sense of belonging through engagement on social media.

Social media and sport researchers often use content analysis, with classifications of certain kinds of data and how it impacts athletes or sport organizations. While such work is beneficial, it often overlooks discourse and meaning embedded within the language used by people on social media. Sveinson and Hoeber (2024) provide compelling work in this direction in their article that analyzes sport fandom and social media discourse. Through critical discourse analysis, they investigate how sport fans use Twitter to create, maintain, and transform cultural boundaries of sport fandom. Their work demonstrates how via social media, fans negotiate boundaries that are simultaneously rigid yet fluid, along with looking at the construction of multiple meanings associated with terms such as loyalty, consumption, and unity. Their research demonstrates the value of using discourse-centered approaches to investigating sport content expressed on social media.

In a similar vein, Winslow et al. (2024) explore the discourse and language expressed on social media through their examination of style expressed by athletes, sport media sites, and intercollegiate athletic departments on social media. Their analysis highlights how discourse about the recruitment of athletes is reflected in an arbitrary and speculative rating system, yet one which is widely shared and understood. They further note that sport and style can be a site for understanding social challenges and how they manifest in discourse around athlete recruitment. Their approach demonstrates the value of rhetorical analysis in sport and social media research, while also highlighting the importance of research into athlete recruitment, given the rise of name, image, and likeness options for athletes within intercollegiate athletics.

Du et al. (2024) discuss machine learning and its applications to research in social media and sport. Through an analysis of methods used in the sport and social media literature along with an empirical investigation of textual data of articles published in IJSC from 2010 to 2020, their research illustrates how machine learning can be used to enhance research rigor and bolster theory development. Given the massive quantity of data that are generated on social media, their research and commentary is most helpful for scholars looking to work with large data sets that are beyond the scope of human-based analysis. Their final section providing directions for future research offers a robust framework from which future inquiry can continue to build using machine learning methodology.

In summary, the articles contained in this special issue of IJSC highlight diversity in topics and methods that speak to the vibrant and dynamic work being conducted in sport and social media research. We anticipate that these articles will be instrumental in assisting sport and social media researchers operating from diverse epistemological frameworks in their efforts to advance both theoretical and applied understanding of social media’s impact and influence on sport.

References

  • Achen, R.M., Stadler-Blank, A., & Sailors, J.J. (2024). I “like” it: The effects of social media platform and message on consumer engagement actions. International Journal of Sport Communication, 17(1).

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  • Bunch, N., Cianfrone, B.A., & Beasley, L. (2024). A critical analysis of coaches’ perceptions of athletic department involvement in team-related social media activism. International Journal of Sport Communication, 17(1).

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  • Cao, Y., Xu, Z., & Matsuoka, H. (2024). Consumer engagement on Weibo in a professional sport context: The case of the Chinese Super League. International Journal of Sport Communication, 17(1).

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  • Du, J., Mamo, Y.Z., Floyd, C., Karthikeyan, N., & James, J.D. (2024). Machine learning in sport social media research: Practical uses and opportunities. International Journal of Sport Communication, 17(1).

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  • Greenhalgh, G., & Goebert, C. (2024). From gearshifts to gigabytes: An analysis of how NASCAR used iRacing to engage fans during the COVID-19 shutdown. International Journal of Sport Communication, 17(1).

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  • Popp, N., Du, J., Shapiro, S.L., & Simmons, J.M. (2024). Using artificial intelligence to detect the relationship between social media sentiment and season ticket purchases. International Journal of Sport Communication, 17(1).

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  • Sveinson, K., & Hoeber, L. (2024). “Be a good fan during the good, the bad, and even the ugly”: Exploring cultural boundaries through sport fan discourses on Twitter. International Journal of Sport Communication, 17(1).

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  • Winslow, L., Browning, B., & Ishak, A.W. (2024). Swag, social media, and the rhetoric of style in college athletic-recruitment discourse. International Journal of Sport Communication, 17(1).

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  • Achen, R.M., Stadler-Blank, A., & Sailors, J.J. (2024). I “like” it: The effects of social media platform and message on consumer engagement actions. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bunch, N., Cianfrone, B.A., & Beasley, L. (2024). A critical analysis of coaches’ perceptions of athletic department involvement in team-related social media activism. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cao, Y., Xu, Z., & Matsuoka, H. (2024). Consumer engagement on Weibo in a professional sport context: The case of the Chinese Super League. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Du, J., Mamo, Y.Z., Floyd, C., Karthikeyan, N., & James, J.D. (2024). Machine learning in sport social media research: Practical uses and opportunities. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Greenhalgh, G., & Goebert, C. (2024). From gearshifts to gigabytes: An analysis of how NASCAR used iRacing to engage fans during the COVID-19 shutdown. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Popp, N., Du, J., Shapiro, S.L., & Simmons, J.M. (2024). Using artificial intelligence to detect the relationship between social media sentiment and season ticket purchases. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sveinson, K., & Hoeber, L. (2024). “Be a good fan during the good, the bad, and even the ugly”: Exploring cultural boundaries through sport fan discourses on Twitter. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Winslow, L., Browning, B., & Ishak, A.W. (2024). Swag, social media, and the rhetoric of style in college athletic-recruitment discourse. International Journal of Sport Communication, 17(1).

    • Crossref
    • Search Google Scholar
    • Export Citation
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