missing data are addressed using inverse probability weights and hierarchical linear models fitted using maximum likelihood procedures. In the qualitative analysis, we use text mining to analyze the results of an open-ended description of the VPGC program, and then, using machine-learning tools, we
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Increasing Awareness of the Importance of Physical Activity and Healthy Nutrition: Results From a Mixed-Methods Evaluation of a Workplace Program
Denny Meyer, Madawa W. Jayawar, Samuel Muir, David Ho, and Olivia Sackett
Through the Perilous Fight: A Case Analysis of Professional Wrestling During the COVID-19 Pandemic
Nicholas P. Davidson, James Du, and Michael D. Giardina
WWE’s latest video game release (#WWE2k20 and #Gaming). Figure 1 —Text-mining results of Twitter contents. Figure 2 displays the results of a sentiment analysis, measuring the extent to which the eight emotional themes (i.e., anger, anticipation, disgust, fear, joy, sadness, surprise, and trust
An Investigation Into the Reasons Physical Education Professionals Use Twitter
Stephen Harvey and Brendon Hyndman
this current study to support the findings from the open-ended questions asked in the final section of the survey. Qualitative data The Leximancer text mining software was utilized to assist researchers in analyzing data generated from the final section of the survey about why the PE professionals used
Chapter 7: An Investigation Into Sports Coaches’ Twitter Use
Stephen Harvey, Obidiah Atkinson, and Brendon P. Hyndman
Purpose: To investigate sports coaches’ Twitter use. Methods: Coaches (N = 310) from 22 countries and a range of sports completed an online survey. Quantitative survey data were analyzed descriptively and triangulated with qualitative data using Leximancer (Brisbane, Queensland, Australia) text mining software. Results: Most participants reported using Twitter for ≥3 years and accessed the platform multiple times per day. More than half participants agreed that using Twitter had positively impacted both their own confidence as a coach and their athletes/players/team’s performance. The strongest overall themes from the qualitative data revealed that Twitter helped sports coaches improve their practices through the sharing of information, connecting with other coaches, and building positivity into their interactions when supporting players. Discussion/Conclusion: Sports coaches perceive Twitter to be a highly valuable platform to network, collaborate, gain access to information, and share ideas and resources.
Applied Sport Business Analytics
Wanyong Choi
, general topics from foundations of analytics for sport managers to natural language processing (NLP), and text mining with practical sport industry examples. Chapter 1 takes the reader through an explanation of the analytics background by discussing the economic and business foundations of sport analytics
What Do Our Words Say? An Analysis of IJSPP Titles
Sophia Nimphius
version of topic modeling, a text-mining term-frequency analysis, provides initial insight and reflection on what our words say about the research we’ve done and the research still left to do. Figure 1 —A lollipop plot of the 20 most frequent words used in titles in IJSPP over the entire history of the
Using Artificial Intelligence to Detect the Relationship Between Social Media Sentiment and Season Ticket Purchases
Nels Popp, James Du, Stephen L. Shapiro, and Jason M. Simmons
detect and identify the taxonomy and salience of social media sentiments. NLP is considered as a special extension of AI innovations ( Wanless et al., 2022 ).The technique is a derivative of several text mining strategies with the ultimate goal of streamlining the process of extracting underlying meaning
Machine Learning in Sport Social Media Research: Practical Uses and Opportunities
James Du, Yoseph Z. Mamo, Carter Floyd, Niveditha Karthikeyan, and Jeffrey D. James
manual . CreateSpace . Wang , H. , Hong , J. , & Guo , Y. ( 2015 , September 7–11 ). Using text mining to infer the purpose of permission use in mobile apps [Proceeding session]. ACM International Joint Conference on Pervasive and Ubiquitous Computing—UbiComp ’15 , Osaka, Japan . https
How the Lack of Content Validity in the Canadian Assessment of Physical Literacy Is Undermining Quality Physical Education
Dean Dudley and John Cairney
assessment of physical literacy: Manual for test administration second edition . https://www.capl-eclp.ca/wp-content/uploads/2017/10/capl-2-manual-en.pdf Hyndman , B. , & Pill , S. ( 2018 ). What’s in a concept? A Leximancer text mining analysis of physical literacy across the international literature
A Social Media Analysis of the Gendered Representations of Female and Male Athletes During the 2018 Commonwealth Games
Elaine Chiao Ling Yang, Michelle Hayes, Jinyan Chen, Caroline Riot, and Catheryn Khoo-Lattimore
). NoSQL refers to “not only Structured Query Language (SQL),” which supports not only relational data but also unstructured data, such as the unstructured Twitter data in this study. MongoDB uses a rich declarative query language to perform text mining, which facilitates the extraction of useful data
