IfI Colloquium: Text Analytics to Support Sense-making in Social Media: A Language-Action Perspective, April 20
, 2017

Speaker: Prof. Yilu Zhou, Ph.D.
Fordham University, U.S.A.

Date: Thursday, April 20, 2017, 17:15 h

Location: BIN 2.A.01

Abstract

Social media and online communities provide organizations with new opportunities to support their business-related functions. 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, organizations are increasingly interested in understanding social media participants’ actions and intentions; however, existing text analytics tools mostly focus on the semantic dimension of language. The Language-Action Perspective (LAP) emphasizes pragmatics; not what people say, but rather, what they do with language. Adopting the design science paradigm, we propose a LAP-based text analytics framework to support sense-making in online discourse. The proposed framework is specifically intended to address the two aforementioned challenges associated with sense-making in online discourse: the need for greater coherence and better understanding of actions. We rigorously evaluate a system developed based on the framework in a series of experiments on a test bed encompassing social media data from multiple channels and industries. The results demonstrate the utility of each individual component of the system, and its underlying framework, in comparison with existing benchmark methods. Furthermore, the results of a user experiment involving hundreds of practitioners, and a four-month field experiment in a large organization, underscore the enhanced sense-making capabilities afforded by text analytics grounded in LAP principles. The results have important implications for online sense-making and social media analytics.

Bio

Yilu Zhou, PhD, is an associate professor at the Gabelli School of Business. Her research interests include business intelligence, web/text/data mining, multilingual knowledge discovery and human-computer interaction. Most specifically, she investigates and explores computational, intelligent and automatic ways to discover interesting and useful patterns in news articles, web sites, forums and other social media. Before joining Fordham University, Dr. Zhou was an assistant professor at George Washington University. She received a PhD in management information systems at the University of Arizona, where she also was a research associate at the Artificial Intelligence Lab. She received her BS in computer science from Shanghai Jiaotong University. Dr. Zhou has published work in academic journals including the Journal of the American Society for Information Science and Technology, IEEE Intelligent Systems and Decision Support Systems. She is a recipient of a NSF grant to study mobile app maturity rating for children. She has taught various courses related to business intelligence, data management and business programming.