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Computing That Serves

Data Mining in Social Media: Reflections, Tips, and Opportunities

Date: 

Thursday, March 12, 2015 - 11:00am

Speaker: 

Geoffrey Barbier

Host: 

Mike Goodrich

Colloquium presented by Dr. Geoffrey Barbier, Senior Computer Scientist at the Air Force Research Laboratory 
Thursday, March 12, 2015 at 11:00 AM
Location: 1170 TMCB

Abstract:
 

Advances in social media changed the way people communicate and offer opportunities for sharing, storing, and analyzing information with fascinating applications.  A statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities.  Social media information itself can be leveraged to realize a useful amount of provenance data for statements in social media. This approach departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" data that can be mined for provenance information and offers interesting research opportunities for data mining in social media and advancing contextual processing.

Biography: 

Geoffrey Barbier attended Brigham Young University from 1987 to 1992. He earned a bachelor’s degree in computer science and minored in aerospace studies. Geoff completed a master’s degree in business administration through Webster University in 2003. He is a 2009 Science, Math, and Research for Transformation (SMART) scholarship recipient and earned his doctoral degree in Computer Science at Arizona State University in Dec 2011. While at Arizona State, he was a student in the Data Mining and Machine Learning (DMML) laboratory. His research interests include human-machine teaming, social computing, and advancing applications for knowledge workers in information saturated domains. His professional experience includes time in the military, work in industry, and civil service. He is currently employed as a senior computer scientist at the Air Force Research Laboratory in Dayton, Ohio.




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