scholarly journals Content mining framework in social media: A FIFA world cup 2014 case analysis

2017 ◽  
Vol 54 (6) ◽  
pp. 786-801 ◽  
Author(s):  
Guilherme M. Thomaz ◽  
Alexandre A. Biz ◽  
Eduardo M. Bettoni ◽  
Luiz Mendes-Filho ◽  
Dimitrios Buhalis
Keyword(s):  
Social Media ◽  
Case Analysis ◽  
World Cup ◽  
Fifa World Cup ◽  
Content Mining

Fragments of us, fragments of them: social media, nationality and US perceptions of the 2014 FIFA World Cup

2014 ◽  
Vol 16 (5-6) ◽  
pp. 726-744 ◽  
Author(s):  
Andrew C. Billings ◽  
Lauren M. Burch ◽  
Matthew H. Zimmerman
Keyword(s):  
Social Media ◽  
World Cup ◽  
Fifa World Cup

scholarly journals Dissertation: “In the intersection of television and Twitter: Social television as a tool for interaction and participation in a media event”

Fachsprache ◽  
2020 ◽  
Vol 42 (1-2) ◽  
pp. 72-75
Author(s):  
Elina Salomaa
Keyword(s):  
Social Media ◽  
Conversation Analysis ◽  
World Cup ◽  
Fifa World Cup ◽  
Broadcast Media ◽  
Television Content ◽  
Digital Discourse ◽  
Media Event ◽  
Shed Light

This dissertation presents the phenomenon of social television by focusing on the interplay between the traditional broadcast media and the newer social media in the context of the FIFA World Cup. The aim of the study is to shed light on interactional practices that are generated in the intersection of television and Twitter. Through the lens of digital discourse and conversation analysis the study examines how the participation in a media event is constructed in live tweeting practices. The dissertation shows that social media have offered new ways of participating and enjoying television content but have not replaced the role of traditional television as a central medium for experiencing massive media events such as the FIFA World Cup.

Selecting the best team from the players in the 2018 FIFA World Cup using performance analysis

2020 ◽  
Vol 42 (1) ◽  
pp. 15-32
Author(s):  
Tugay Karadag ◽  
Coskun Parim ◽  
Erhan Cene
Keyword(s):  
Performance Analysis ◽  
Topsis Method ◽  
World Cup ◽  
Fifa World Cup ◽  
Performance Variables

This study aims to determine the best player in each position from among the footballers who played in the 2018 World Cup in Russia. Player statistics for those who played over 200 minutes were obtained from the FIFA official and transfermarkt.com websites. Selected performance variables were then calculated per 100 minutes and the results were normalised. Kruskal Wallis H and Bonferroni Tests were used to determine the weights of the variables before the analysis. As the variables will have different values according to the players’ positions, the weights for each position were calculated separately. Finally, the performances of the players on the basis of the variables used were ranked for each position using the TOPSIS method. A second analysis was undertaken including only those players whose ages were under 28 and goalkeepers whose ages were under 32. The purpose of this analysis was to identify players with potential that had been largely unrecognised up until the tournament. It was found that both the teams selected in this way were dominated by players from European clubs. Ninety-two percent of the top sixty players in the analysis were playing in European leagues with 85% playing in Spain, England, Italy, Germany, France or Russia.

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