Is it really about me?: message content in social awareness streams
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Chatter on the red: what hazards threat reveals about the social life of microblogged information
Proceedings of the 2010 ACM conference on Computer supported cooperative work
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Hip and trendy: Characterizing emerging trends on Twitter
Journal of the American Society for Information Science and Technology
Identifying relevant social media content: leveraging information diversity and user cognition
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
Finding and assessing social media information sources in the context of journalism
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Dynamics of personal social relationships in online social networks: a study on twitter
Proceedings of the first ACM conference on Online social networks
Are Some Tweets More Interesting Than Others? #HardQuestion
Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval
Deep Twitter diving: exploring topical groups in microblogs at scale
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Social media platforms such as Twitter garner significant attention from very large audiences in response to real-world events. Automatically establishing who is participating in information production or conversation around events can improve event content consumption, help expose the stakeholders in the event and their varied interests, and even help steer subsequent coverage of an event by journalists. In this paper, we take initial steps towards building an automatic classifier for user types on Twitter, focusing on three core user categories that are reflective of the information production and consumption processes around events: organizations, journalists/media bloggers, and ordinary individuals. Exploration of the user categories on a range of events shows distinctive characteristics in terms of the proportion of each user type, as well as differences in the nature of content each shared around the events.