The experienced "sense" of a virtual community: characteristics and processes
ACM SIGMIS Database
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Empirical comparison of algorithms for network community detection
Proceedings of the 19th international conference on World wide web
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Detecting Community Kernels in Large Social Networks
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
The Joint Inference of Topic Diffusion and Evolution in Social Communities
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Unfolding the event landscape on twitter: classification and exploration of user categories
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
Inferring who-is-who in the Twitter social network
Proceedings of the 2012 ACM workshop on Workshop on online social networks
Cognos: crowdsourcing search for topic experts in microblogs
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Defining and evaluating network communities based on ground-truth
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
It's Not in Their Tweets: Modeling Topical Expertise of Twitter Users
SOCIALCOM-PASSAT '12 Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust
Distinguishing topical and social groups based on common identity and bond theory
Proceedings of the sixth ACM international conference on Web search and data mining
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We present a semantic methodology to identify topical groups in Twitter on a large number of topics, each consisting of users who are experts on or interested in a specific topic. Early studies investigating the nature of Twitter suggest that it is a social media platform consisting of a relatively small section of elite users, producing information on a few popular topics such as media, politics, and music, and the general population consuming it. We show that this characterization ignores a rich set of highly specialized topics, ranging from geology, neurology, to astrophysics and karate - each being discussed by their own topical groups. We present a detailed characterization of these topical groups based on their network structures and tweeting behaviors. Analyzing these groups on the backdrop of the common identity and bond theory in social sciences shows that these groups exhibit characteristics of topical-identity based groups, rather than social-bond based ones.