Doctoral defence: Shakshi Sharma “Fighting Misinformation in the Digital Age: A Comprehensive Strategy for Characterizing, Identifying, and Mitigating Misinformation on Online Social Media Platforms“

On 6. October at 5pm Shakshi Sharma will defend her doctoral thesis "Fighting Misinformation in the Digital Age: A Comprehensive Strategy for Characterizing, Identifying, and Mitigating Misinformation on Online Social Media Platforms" for obtaining the degree of Doctor of Philosophy (Computer Science).

Supervisor:
Assoc. Prof. Rajesh Sharma, University of Tartu

Opponents:
Assoc. Prof. Joydeep Chandra, Indian Institute of Technology, Patna (India);
Assist. Prof. Kiran Garimella, Rutgers University (USA).

Summary
The emergence of Online Social Media (OSM) platforms like Twitter and Facebook has facilitated the global dissemination of false information, contributing to social fear, anxiety, and economic harm. This thesis examines the multifaceted approach to combating misinformation in the digital era, focusing on three key dimensions: identifying misinformation content, developing a framework for identifying misinformation spreaders, and carrying out effective counter misinformation measures.

First, our proposed characterization approach aims to understand the traits of rumor and non-rumor posts to identify cognitive behavior and motivations behind spreading misinformation. Scrutinizing social media posts' characteristics helps the research community detect and prevent misinformation.

Second, previous techniques for detecting suspicious or malicious users and identifying misinformation on platforms like Twitter have not considered user-level detection adequately. Categorizing a user as a rumor based on one post is insufficient. Our contribution is a classification framework that combines multiple posts and network information to develop a better approach.

Third, existing approaches for mitigating the spread of misinformation on social media have limitations, such as the lack of external moderation and reliance on strict assumptions. We propose an automated rebuttal of misinformation at scale by harnessing social media data and curated fact-checked data repositories. Particularly, this dimension focuses on the Twitter platform and COVID-19 misinformation, exploring two complementary approaches.

The defence can also be followed in Zoom  (Meeting ID: 921 8942 7454, Passcode: ati).