Topic Modeling in Social Streams

Using social media to conduct commerce is challenging for businesses since it requires constant monitoring of the real-time stream for topics of interest. As part of davai we developed a sophisticated module to automate the monitoring process by using a topic-modeling approach:

  1. A user would register interest by creating a topic, labels it and adds keywords,
  2. System analyzes filtered messages, detects topic and adapts filter so that it stays current (versus topic drift and trending topics),
  3. Social network effect to address new topic discovery.


The challenge of topic modeling in social streams is twofold: messages (documents) even if aggregated are too small to create meaningful models and new topics are constantly published that could be of interest to a user.

Our approach leverages the network structure of user:

  • Connected users that share interests and influence each other are more similar,
  • Merge user’s stream with authored stream of his friends of friends,
  • Use ranking to find authoritative users with similar interest.

The topic modeling approach was the base for further research at the University of Washington by Professor Ankur and can be found in: “SocialLDA: Scalable Topic Modeling in Social Networks”.