Ahmed Abbasi, Ph.D.,
Assistant Professor of Information Technology, McIntire School of Commerce, University of Virginia
Social Media Analytics
November 9, 2012
3:00 p.m. - 4:30 p.m.
Room 2-206 Carlson School of Management
The rapid growth of social media and online communities has dramatically changed the manner in which communication takes place. Organizations are increasingly utilizing general-purpose social media technologies to support their business-related functions. According to a recent McKinsey Quarterly report, 50% of the more than 1,700 organizations surveyed are using social networking, 41% are using blogs, 25% are using wikis and 23% are using micro blogs. Moreover, these numbers have more than doubled in the past four years. Web 2.0 technologies are being leveraged for internal purposes, customer-related purposes, and in working with external suppliers and partners. Organizations are deriving considerable benefits from their use, including increased speed of access to knowledge, enhanced identification of experts, increased number of successful innovations, and reduced communication and operational costs.
Social media analytics is the process of analyzing such content to derive important business insights. It is a useful mechanism for evaluating the effectiveness of organizations' social media initiatives. Moreover, social media analytics can be used to derive insights from independent user-generated content. This presentation provides an overview of how organizations are using social media analytics to drive significant business value. Application areas discussed include:
- The relation between online sentiments and financial performance
- The use of analytics to assess online customer engagement
- Using social media to inform decision-making
- Social listening: real-time monitoring of social media
The presentation also describes various challenges associated with social media analytics, including online information quality problems, context issues pertaining to predictive analytics, and sense-making limitations associated with the analysis of online text.
Ahmed Abbasi is an assistant professor of Information Technology in the McIntire School of Commerce at the University of Virginia. He received his Ph.D. in Information Systems from the University of Arizona, where he also served as a research associate and project lead in the Artificial Intelligence Lab. Ahmed has over ten years of experience pertaining to predictive analytics, with particular emphasis on text and social media. He serves on program committees for various conferences related to computational linguistics and text analytics. Ahmed's research has been funded through multiple grants from the National Science Foundation. He has published nearly 40 peer-reviewed articles in journals and conferences. One of his articles was considered a top publication for 2010 by the Association for Information Systems. Ahmed's work has also been featured in various media outlets, including the Wall Street Journal, the Associated Press, and Fox News.