Concurrent Bursty Behavior of Social Sensors in Sporting Events
Yuki Takeichi, Kazutoshi Sasahara, Reji Suzuki, and Takaya Arita

TL;DR
This study investigates how Twitter users act as social sensors during sporting events, showing that burst patterns of tweets and retweets can indicate game outcomes and reveal interaction dynamics among users.
Contribution
It demonstrates that concurrent burst analysis of tweets and retweets can predict game results and uncovers the structure of social sensor networks across cultures.
Findings
Burst patterns correlate with game outcomes.
Retweet networks show user clusters by team.
Social sensors exhibit scale-free network properties.
Abstract
The advent of social media expands our ability to transmit information and connect with others instantly, which enables us to behave as "social sensors." Here, we studied concurrent bursty behavior of Twitter users during major sporting events to determine their function as social sensors. We show that the degree of concurrent bursts in tweets (posts) and retweets (re-posts) works as a strong indicator of winning or losing a game. More specifically, our simple tweet analysis of Japanese professional baseball games in 2013 revealed that social sensors can immediately react to positive and negative events through bursts of tweets, but that positive events are more likely to induce a subsequent burst of retweets. We also show that these findings hold true across cultures by analyzing tweets related to Major League Baseball games in 2015. Furthermore, we demonstrate active interactions…
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