Mr Mahdi Latifi Fard, Dr Marjan Saffari,
Volume 11, Issue 22 (12-2021)
Abstract
Fans like to talk about their favorite team and players with others. Professional team fans use social media to learn more about teams, connect with other fans, follow teams and players, and build a fan community. Social media by creating a network of users has become a platform for researchers to study fan behavior. Given that members of the fan community interact with each other, their opinions on social media also has determined relation to each other. The present study to understand and discover the relationship between fans 'opinions of El Clásico, used the network approach. In this study, Facebook was selected as the research platform to analyze the media consumption of fans about the El Clásico in the 2017-18 season. Finally, fan comments were divided into 14 categories. The results showed that the three nodes of "references to the team", "references to the individual" and "references to the game" are the most important categories that have kept the network of dialogue between the fans dynamic. While these three nodes of "references to the team", "references to the individual" and "references to the game" are important structurally and network-wise , but from a behaviorism point of view, team identification plays a key role in creating such a network. This means that the underlying role of the "use of us and them" node in the network of opinions is certain.
Mohammad Mehdi Kheirkhiz, Behrouz Abdoli, Lorenzo Laporta, Alireza Farsi,
Volume 100, Issue 100 (10-2020)
Abstract
The present study aims to investigate the variables of social networks in different positions in basketball. These variables were applied in two levels of analysis: micro (individual) and macro (global interaction of the team). 24 official Chemidoor Club competitions in the 2020 men's Iranian Premier League were selected by available sampling. This research analyzed the network properties of Degree, Betweenness, Closeness, Eigenvector, and Density centrality across teams and positions. The one-way ANOVA for the factor position in the micro-level found statistical differences between the game positions in the dependent variables of Dc: (F(4,15)= 61/29, p= 0/000), Bc: (F(4,15)= 210/11, p= 0/000), Cc: (F(4,15)= 78/55, p= 0/000). However, no significant difference was observed in the Eig: (F (4, 15) = 1/58, p= 0/184). Results of post hoc test indices were significantly different between position 1 (point guard) and other positions. Macro-level team density analysis showed a significant difference between performance results in successful and unsuccessful. The guard player role was observed as the situation that establishes the most interactions with teammates during the competition. Therefore, players with higher degrees were not the ones assisting the most shots. The other players with higher degrees were not the ones assisting the most shots. These results may be used as a tool for coaching to improve their teams’ strategies in concrete, measurable ways.
