LinkLog: Incremental Discovery of Knowledge

From this Incremental Knowledge Discovery in Online Social Media by Xuning Tang

In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge.

This dissertation centers on the issue of modeling the dynamics of user communities, trending stories, topics and user interests in online social media. However, knowledge discovery and management in online social media is challenging because: 1) social media data arrive in the form of continuous streams; 2) the volume of social media data is potentially infinite; and 3) more importantly, social media data is very complex which consists of network, text, tag, click and other information.

┬ávia Google Scholar Alert on “Topic Modeling”