SBIR-STTR Award

The past decade has seen an explosion in online social media, such as blogs, forums, twitter, and so forth. This online information can give us insights into groups and communities--what are their "hot button" issues, how are they responding to current events, and how are they likely to react in the future. With the advance and proliferation of technology, online groups and communities now include populations of high importance to the U.S. military planners, such as students in Iran, social conservatives in Saudia Arabia, and housewives in Egypt -- all sorts of groups throughout the Middle East. Currently, there is a great deal of information in social media that could be exploited for the benefit of military planners, but it is infeasible to monitor social media channels and provide simple, realtime assessment, analysis and predictive capabilities. This is the problem which we address in this proposal.

Keywords:
Dynamic Social Network Analysis, Dynamic Group Dynamics, Text Mining, Topic Detection, Social Network Mining, Machine Learning, Predictive Modeling

The goal in this project is to develop GroupPulse, a system that enables decision-makers to gain insights from online communities. To do this, the system will monitor one or more social media streams, identify and track groups and sub-communities, and provide realtime analysis of group dynamics and topics. While current technologies can address some of the key capabilities needed for GroupPulse, they do not easily integrate nor do they individually provide the scalability needed for our vision. Specifically, in order to realize the GroupPulse vision, we need to integrate community detection algorithms, text mining methods to identify topics and sub-topics as they are mentioned in the social media streams, and models of group dynamics to monitor topics of interest in a group and how those shift over time.

Keywords:
Social Media, Social Network Analysis, Text Mining, Data Mining, Behavioral Modeling, Topic Detection, Entity Resolution