On Social Media, Your Toughest Rival Plays on Your Own Team

STUDYING TWEETS REGARDING FEMALE SOCCER PLAYERS IN THE US, ROSSI AND RUBERA FOUND THAT RIVALRY AMONG ATHLETES SPILLS OVER ONTO THE VIRTUAL FIELD, BUT WITH DIFFERENT RULES: COMPETITION COMES MOSTLY FROM PLAYERS THAT SHARE THE SAME CHARACTERISTICS

Athletes today do not only compete on the field; they also compete on social media platforms, such as Twitter, as Federico Rossi and Gaia Rubera (Department of Marketing) found out in a recent study. And the competition is among players with similar characteristics: the tougher rivals play on your own team, as Professor Rossi highlights in a video.
 
The authors studied how a particular group of users decide to create content – to write tweets in this case – about the players of the National Women’s Soccer League in the US. They noticed that it’s not only the performance of the players on the field that affects the decision to write content about them, but also their behavior on Twitter, the investigated platform.
 
They observed that whenever a player writes a tweet she’s able to increase the number of tweets that she receives by about 25%. But this increase doesn’t only come from an increase in the demand – the total number of tweets the fans decide to write – it comes in part at the expense of other players. “So basically the players are competing for a group of tweets that are out there and of course this competition comes mostly from players that share the same characteristics,” Rossi says. Athletes that play for the same team, for example, suffer from competition more than those that play on rival teams.
 
Every time an athlete tweets, on the one hand total audience for the sport rises, on the other the audience for athletes similar to the one tweeting is eroded.
 
What Rossi and Rubera are trying to discover now is whether other characteristics are playing a role in this kind of competition, for example the attractiveness of a player, or her age or other personal characteristics.
 
In general these types of studies are considered big-data research not because of the size of the database used (millions of observations, however), but mainly because of the microeconomic detail of the data.

 

by Fabio Todesco