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Social media sites such as Twitter, Tubmlr and Facebook can anonymize the identity of a user, while at the same time enabling them to relate a wide variety of information, comment and opinion. The sometimes spurious link between on-line identity and the message portrayed can be used to impersonate real or fictional personalities, occasionally providing a seeming credible account of current news and events.
However, a recent paper published by John D. Burger and colleagues suggests that a persons use of language can betray certain aspects of their (hidden) identity, most notably their gender.
Their study, entitled “Discriminating Gender on Twitter”, looks at how randomly selected twitter updates (tweets), can identify the gender of a user to an accuracy of approximately 70% [3].
Aside from garnering unwarranted credibility, self-anonymization can lead to a breakdown of social norms, as disentangling a persons “good name” from their identity has been shown to cause them to act with a lessened sense of responsibility [4]. Although the use of language can suggest certain demographic features, it may provide a useful insight into user behaviour when combined with more traditional social network analysis methods.