Tweets to Touchdowns: Predicting National Football League Achievement from Social Media Optimism

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National Football League Achievement from Social Media Optimism</title> <meta name="description" content="Tweets to Touchdowns: Predicting National Football League Achievement from Social Media Optimism"> <meta name="keywords" content="National Football League, NFL, NFL Draft, sentiment analysis, Reddit, social media, NLP, sentiment analysis."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Tweets to Touchdowns: Predicting National Football League Achievement from Social Media Optimism"> <meta name="citation_author" content="Rohan Erasala"> <meta name="citation_author" content="Ian McCulloh"> <meta name="citation_publication_date" content="2024/11/11"> <meta name="citation_journal_title" content="International Journal of Sport and Health Sciences"> <meta name="citation_volume" content="18"> <meta name="citation_issue" content="11"> <meta 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href="https://publications.waset.org/search?q=Rohan%20Erasala">Rohan Erasala</a>, <a href="https://publications.waset.org/search?q=Ian%20McCulloh"> Ian McCulloh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>The National Football League (NFL) Draft is a chance for every NFL team to select their next superstar. As a result, teams heavily invest in scouting, and millions of fans partake in the online discourse surrounding the draft. This paper investigates the potential correlations between positive sentiment in individual draft selection threads from the subreddit r/NFL and if these data can be used to make successful player recommendations. It is hypothesized that there will be limited correlations and nonviable recommendations made from these threads. The hypothesis is tested using sentiment analysis of draft thread comments and analyzing correlation and precision at k of top scores. The results indicate weak correlations between the percentage of positive comments in a draft selection thread and a player’s approximate value, but potentially viable recommendations from looking at players whose draft selection threads have the highest percentage of positive comments.</p> <iframe src="https://publications.waset.org/10013885.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=National%20Football%20League" title="National Football League">National Football League</a>, <a href="https://publications.waset.org/search?q=NFL" title=" NFL"> NFL</a>, <a href="https://publications.waset.org/search?q=NFL%20Draft" title=" NFL Draft"> NFL Draft</a>, <a href="https://publications.waset.org/search?q=sentiment%20analysis" title=" sentiment analysis"> sentiment analysis</a>, <a href="https://publications.waset.org/search?q=Reddit" title=" Reddit"> Reddit</a>, <a href="https://publications.waset.org/search?q=social%20media" title=" social media"> social media</a>, <a href="https://publications.waset.org/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/search?q=sentiment%20analysis." title=" sentiment analysis."> sentiment analysis.</a> </p> <a href="https://publications.waset.org/10013885/tweets-to-touchdowns-predicting-national-football-league-achievement-from-social-media-optimism" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/10013885/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/10013885/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/10013885/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/10013885/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/10013885/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/10013885/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/10013885/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/10013885/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/10013885/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/10013885/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/10013885.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">14</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Richter, F. (2022, September 6). Infographic: Americans love the NFL, but change is looming. Statista Daily Data. https://www.statista.com/chart/15869/favrotie-sports-league/ <br>[2] Lewis, J. (2023, April28). NFL draft viewership rebounds from last year. Sports Media Watch. https://www.sportsmediawatch.com/2023/04/nfl- draft-viewership-increase-espn-abc-nfl-network-first-round/ <br>[3] Kraeutler, M. J., Carver, T. J., Belk, J. W., & McCarty, E. C. (2018). What is the value of a national football league draft pick? An analysis based on changes made in the collective bargaining agreement. The Journal of Strength & Conditioning Research, 32(6), 1656-1661. <br>[4] Johnson, R. (2018, April 12). How much does it cost a team to scout a top NFL prospect?. SBNation.com. https://www.sbnation.com/college- football/2018/4/12/17193092/cost-to-scout-an-nfl-prospect <br>[5] Rizzuti, A. (2023, July 12). Bryce Young remains amongst NFL’s top 10 jersey sellers through June. USA Today. https://pantherswire.usatoday.com/lists/nfl-jersey-sales-top-10-june- bryce-young-tom-brady-patrick-mahomes-aaron-rodgers/ <br>[6] Lopez-Gonzalez, H., & Griffiths, M. D. (2018). Betting, forex trading, and fantasy gaming sponsorships—a responsible marketing inquiry into the 'gamblification' of English football. International Journal of Mental Health and Addiction, 16(2), 404-419. <br>[7] Humphreys, B. R., & Perez, L. (2020). Sports betting, sports bettors and sports gambling policy. Sport Management Review, 23(1), 1-7. <br>[8] Martin, R. J., & Nelson, S. (2020). Fantasy sports, real money: Exploration of the relationship between fantasy sports participation and sports betting. Journal of Gambling Studies, 36(1), 193-209. <br>[9] Drayer, J., & Rascher, D. A. (2019). Fantasy football’s potential influence on NFL fan engagement and sports betting decisions. Sport Management Review, 22(3), 350-362. <br>[10] Weiss, M. B., & Loeb, S. E. (2021). The impact of fantasy sports on television viewership and online sports betting. Journal of Media Economics, 34(1), 26-45. <br>[11] Cohen, D. (2020, April 24). Sports twitter awakens during round 1 of the 2020 NFL draft. Adweek. https://www.adweek.com/performance- marketing/sports-twitter-awakens-during-round-1-of-the-2020-nfl-draft/ <br>[12] Lutz, R. (2015). Fantasy football prediction. arXiv preprint arXiv:1505.06918. <br>[13] Whiting, S. W., & Maynes, T. D. (2016). Selecting team players: Considering the impact of contextual performance and workplace deviance on selection decisions in the National Football League. Journal of Applied Psychology, 101(4), 484. <br>[14] King, N. A. (2017). Predicting a Quarterback's Fantasy Football Point Output for Daily Fantasy Sports Using Statistical Models (Doctoral dissertation). Arlington, TX: University of Texas at Arlington <br>[15] Lyons, B. D., Hoffman, B. J., Michel, J. W., & Williams, K. J. (2011). On the predictive efficiency of past performance and physical ability: The case of the National Football League. Human Performance, 24(2), 158-172. <br>[16] Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6), 1-4. <br>[17] Brabham, D. C. (2008). Crowdsourcing as a model for problem s <br>[18] Clavio, G., & Kian, E. M. (2010). Uses and gratifications of a retired female athlete's Twitter followers. International Journal of Sport Communication, 3(4), 485-500. <br>[19] Hambrick, M. E. (2017). Social media in sports: A narrative review of research on social media in sport and physical activity. The Physical Educator, 74(3), 439. <br>[20] Xu, Z., Frankwick, G. L., & Ramirez, E. (2019). Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective. Journal of Business Research, 94, 61-74. <br>[21] Reed, A., Piorkowski, J., & McCulloh, I. (2018). Correlating NBA team network centrality measures with game performance. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (pp. 1291-1294). IEEE. <br>[22] Wiseman, J. (2020). Monitoring Public Sentiment of NFL Draft Picks via Machine Learning Techniques. <br>[23] Silva, G. H. D. S. (2021). Football players performance analysis and formal/informal media: Sentiment analysis and semantic similarity (Master’s thesis). <br>[24] Sinha, S., Dyer, C., Gimpel, K., & Smith, N. A. (2013). Predicting the NFL using Twitter. arXiv preprint arXiv:1310.6998. <br>[25] Perez, J. M., Rajngewerc, M., Giudici, J. C., Furman, D. A., Luque, F., Alemany, L. A., & Mart ́ınez, M. V. (2023). pysentimiento: A Python Toolkit for Opinion Mining and Social NLP tasks. <br>[26] Taboada, M. (2016). Sentiment analysis: An overview from linguistics. Annual Review of Linguistics, 2, 325-347. <br>[27] Approximate value. Pro Football Reference. 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Tweets to Touchdowns: Predicting National Football League Achievement from Social Media Optimism