Ahmed Abbasi, McIntire School of Commerce


Ahmed Abbasi, McIntire School of Commerce

Friday, October 28th, 2016 at 3:30 pm

Rice Hall Auditorium

Host: Hongning Wang

Text Analytics to Support Sense-making in Social Media:

A Language-Action Perspective

This presentation summarizes the results from a five-year text analytics project examining social media sense-making capabilities in various industries, including telecommunications, health, and security. Despite their various benefits, social media technologies present two important challenges for sense-making. First, online discourse is plagued by incoherent, intertwined conversations that are often difficult to comprehend. Moreover, existing text analytics tools mostly focus on the semantic dimension of language, as opposed to actr ability to perform many basic social media analytics tasks such as identifyions and intentions. I use real-world examples to illustrate how these challenges inhibit ouing important participants, issues, and ideas. The Language-Action Perspective (LAP) emphasizes pragmatics; considering conversations, actions, and context. In order to address the two aforementioned challenges, we developed a LAP-based text analytics framework to support sense-making in online discourse. I present evaluation results from multiple social media channels and industries, including an extended field experiment utilizing a large cloud-based system developed based on the framework. The results have important implications for online sense-making, social media analytics, and how we think about text.

Ahmed Abbasi is Murray Research Professor and associate professor of Information Technology in the McIntire School of Commerce at the University of Virginia. He is Director of the Center for Business Analytics and coordinator for the Enterprise IT Management module of the MS in MIT executive degree program. Ahmed is also a member of the Predictive Analytics Lab. Ahmed received his Ph.D. in Information Systems from the University of Arizona, where he also worked as a project-lead on multi-million dollar “big data” initiatives in the Artificial Intelligence Lab. He attained an M.B.A. and B.S. in Information Technology from Virginia Tech.

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