School of Electrical, Computer and Energy Engineering
Ph.D. Final Oral Defense
Facilitating Efficient Information Seeking in Social Media
by
Suhas Ranganath
10/18/2017
9:00 AM
BYENG 420
Committee:
Dr. Huan Liu (Co-chair)
Dr. Ying-Cheng Lai (Co-chair)
Dr. Hanghang Tong
Dr. Roman Vaculin
Abstract
Online social media is popular due to its real-time nature, seamless connectivity and a large user base. This motivates users to employ social media for seeking information by reaching out to their large number of social connections. Information seeking can in the form of requests for personal and time-critical information or gathering perspectives on important issues. Social media platforms are not designed for resource seeking and experience large volumes of messages, leading to requests not being fulfilled satisfactorily. Designing frameworks to facilitate efficient information seeking in social media will help users to obtain appropriate assistance for their needs and help platforms to increase user satisfaction.
Several challenges exist in the way of facilitating information seeking in social media. First, the characteristics affecting the user’s response time for a question are not known, making it hard to identify prompt responders. Second, the social context in which the user has asked the question has to be determined to find personalized responders. Third, users employ rhetorical requests, which are statements having the syntax of questions, and systems assisting information seeking might be hindered from focusing on genuine questions. Social media advocates of political campaigns try to shape user opinion, by employing nuanced message construction and propagation strategies to preventing users from obtaining balanced perspectives on issues of public importance.
Socioeconomic and linguistic studies on user behavior while making or responding to information seeking requests provides concepts drawing from which we can address these challenges. We propose methods to estimate the response time of the user for a given question to identify prompt responders. We compute the question specific social context an asker shares with his social connections to identify personalized responders. We identify rhetorical questions by modeling user motivations to post them. We then draw from theories of political mobilization to model the behaviors arising from the strategies used by advocates to identify their accounts.