Abstract. A particular challenge in the area of social media analysis is how to find communities within a larger network of social interactions. Here a community may be a group of microblogging users who post content on a coherent topic, or who are associated with a specific event or news story. Twitter provides the ability to curate users into lists, corresponding to meaningful topics or themes. Here we describe an approach for crowdsourcing the list building efforts of many different Twitter users, in order to identify topical communities. This approach involves the use of ensemble community finding to produce stable groupings of user lists, and by extension, individual Twitter users. We examine this approach in the context of a case study surrounding the detection of communities on Twitter relating to the London 2012 Olympics.
In related work, the authors proposed an approach to identify topical communities of high-profile users on Twitter, by aggregating their list memberships and applying overlapping community finding REF .
Identifying Topical Twitter Communities via User List Aggregation
ArXiv
ArXiv
Computer Science Physics