Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football

Weimar D, Soebbing BP, Wicker P (2021)
Journal of Sport Management 35(3): 266-277.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Weimar, Daniel; Soebbing, Brian P.; Wicker, PamelaUniBi
Abstract / Bemerkung
The identification of relevant effects is challenging in Big Data because larger samples are more likely to yield statistically significant effects. Professional sport teams attempting to identify the core drivers behind their follower numbers on social media also face this challenge. The purposes of this study are to examine the effects of game outcomes on the change rate of followers using big social media data and to assess the relative impact of determinants using dominance analysis. The authors collected data of 644 first division football clubs from Facebook (n = 297,042), Twitter (n = 292,186), and Instagram (n = 312,710) over a 19-month period. Our fixed-effects regressions returned significant findings for game outcomes. Therefore, the authors extracted the relative importance of wins, draws, and losses through dominance analysis, indicating that a victory yielded the highest increase in followers. For practitioners, the findings present opportunities to develop fan engagement, increase the number of followers, and enter new markets.
Erscheinungsjahr
2021
Zeitschriftentitel
Journal of Sport Management
Band
35
Ausgabe
3
Seite(n)
266-277
ISSN
0888-4773
eISSN
1543-270X
Page URI
https://pub.uni-bielefeld.de/record/2951656

Zitieren

Weimar D, Soebbing BP, Wicker P. Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football. Journal of Sport Management. 2021;35(3):266-277.
Weimar, D., Soebbing, B. P., & Wicker, P. (2021). Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football. Journal of Sport Management, 35(3), 266-277. https://doi.org/10.1123/jsm.2020-0275
Weimar, Daniel, Soebbing, Brian P., and Wicker, Pamela. 2021. “Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football”. Journal of Sport Management 35 (3): 266-277.
Weimar, D., Soebbing, B. P., and Wicker, P. (2021). Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football. Journal of Sport Management 35, 266-277.
Weimar, D., Soebbing, B.P., & Wicker, P., 2021. Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football. Journal of Sport Management, 35(3), p 266-277.
D. Weimar, B.P. Soebbing, and P. Wicker, “Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football”, Journal of Sport Management, vol. 35, 2021, pp. 266-277.
Weimar, D., Soebbing, B.P., Wicker, P.: Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football. Journal of Sport Management. 35, 266-277 (2021).
Weimar, Daniel, Soebbing, Brian P., and Wicker, Pamela. “Dealing with statistical significance in Big Data: The social media value of game outcomes in professional football”. Journal of Sport Management 35.3 (2021): 266-277.
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