Understanding the impacts of fake news and misinformation on social media

About this project

Project description

Users face challenges of preserving their preferences when interacting with other community members. These interactions also get infiltrated by the fake news and misinformation campaigns pursued by bots or other social media users. Using machine learning and NLP techniques, we aim to build a theoretical model for explaining behavioral changes in online communities and explore how online discourses and fake news impact them. We will carry mix-method research to analyze data from popular social media on a sociopolitical topic, applying tools from NLP and network science. We will uncover the nuances of user interaction and the roles played by fake news and misinformation campaigns. This project builds upon the existing theories in the information systems and requires engaging in both the qualitative and quantitative methods.

Outcomes

Familarity with information systems research, programing using Python, background in machine learning and statistics

Information for applicants

Essential capabilities

Familarity with information systems research, programing using Python, background in machine learning and statistics

Desireable capabilities

Comfortable with both quantitative and qualitative research methods.

Expected qualifications (Course/Degrees etc.)

Masters in related fields, research experience.

Project supervisors

Principal supervisors

UQ Supervisor

Assistant professor Bikesh Raj Upreti

UQ Business School
IITD Supervisor

Professor Arpan Kar

Department of Management Studies
Additional Supervisor

Associate professor Stan Karanasios

UQ Business School