A UK-based online questionnaire investigating aspects of usage of user-generated media (UGM), such as Facebook, LinkedIn and Twitter, attracted 587 participants. Results show a high degree of engagement with social networking media such as Facebook, and a significant engagement with other media such as professional media, microblogs and blogs. Participants who experience information overload are those who engage less frequently with the media, rather than those who have fewer posts to read. Professional users show different behaviours to social users. Microbloggers complain of information overload to the greatest extent. Two thirds of Twitter-users have felt that they receive too many posts, and over half of Twitter-users have felt the need for a tool to filter out the irrelevant posts. Generally speaking, participants express satisfaction with the media, though a significant minority express a range of concerns including information overload and privacy.
Social-graph services such as Facebook and LinkedIn enforce relationship reciprocity by requiring that both parties consent to being linked. By doing this, Twitter has allowed a fascinating evolution to take place, from a social-based small messaging service to a highly versatile social environment, finding its niche as the main interest-graph medium but not limited to that. Naaman @cite_16 found over 40 , posts by a user describing what they are currently doing, in the manner encouraged by the "what's happening" prompt. Next most common were statements and random thoughts, opinions and complaints and information sharing such as links, each taking over 20 . Less common tweet themes were self-promotion, questions to followers, presence maintenance e.g. "I'm back!", anecdotes about oneself and anecdotes about another. Messages posted from mobile devices are more likely to be "me now" messages (51 "me now" messages than males. A relatively small number of people undertake information sharing as a major activity; users can be grouped into "informers" and "meformers", where meformers mostly share information about themselves. Informers and meformers differ in various ways. Informers tend to be more conversational and have more contacts.
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In this work we examine the characteristics of social activity and patterns of communication on Twitter, a prominent example of the emerging class of communication systems we call "social awareness streams." We use system data and message content from over 350 Twitter users, applying human coding and quantitative analysis to provide a deeper understanding of the activity of individuals on the Twitter network. In particular, we develop a content-based categorization of the type of messages posted by Twitter users, based on which we examine users' activity. Our analysis shows two common types of user behavior in terms of the content of the posted messages, and exposes differences between users in respect to these activities.