Users sleeping time analysis based on micro-blogging data

The emergence of new social network services, often labeled as Web 2.0, has permitted an amazingly increase of user generated content. In particular, Sina Weibo, a popular Chinese micro-blogging service is designed as platforms allowing users to generate contents that open to the public. From analyzing activates of submitting posts to Sina Weibo, some features of users can be estimated. This paper aims to contribute to this growing body of literature by studying how users' frequent activities reflect their sleeping time and living time zones. By mining a large set of users' activates data from Sina Weibo, we demonstrate its possible role to detect the sleeping time of users and find a new method for judging users' time zone.