Inferring who-is-who in the Twitter social network

Naveen Kumar Sharma, Saptarshi Ghosh, Fabricio Benevenuto, Niloy Ganguly, Krishna Gummadi
2012 Computer communication review  
In this paper, we design and evaluate a novel who-is-who service for inferring attributes that characterize individual Twitter users. Our methodology exploits the Lists feature, which allows a user to group other users who tend to tweet on a topic that is of interest to her, and follow their collective tweets. Our key insight is that the List meta-data (names and descriptions) provides valuable semantic cues about who the users included in the Lists are, including their topics of expertise and
more » ... ow they are perceived by the public. Thus, we can infer a user's expertise by analyzing the meta-data of crowdsourced Lists that contain the user. We show that our methodology can accurately and comprehensively infer attributes of millions of Twitter users, including a vast majority of Twitter's influential users (based on ranking metrics like number of followers). Our work provides a foundation for building better search and recommendation services on Twitter.
doi:10.1145/2377677.2377782 fatcat:cbvngvdhvncrdns2q5hrmypxoe