PhD students, University of Manchester

Scholarship: Fully funded
Qualifications: Bachelor’s degree, Master’s degree
Subjects: Data Analysis
Nationality: International Students
Closing date: April 9th
Start date: immediately

Scholarship Description:

Data analytics to address fake news and deepfakes in social networks.

Fake news and deepfakes, which are new types of maliciously generated audio, video or image disinformation, can have significant negative effects on society. During the COVID-19 crisis, for example, the spread of various types of fake news through social media and social networks has jeopardized the effectiveness of non-pharmaceutical interventions and undermined the credibility of scientific evidence on vaccination. Identifying, analyzing, and mitigating the social effects of fake news and deepfakes in social networks pose unique and urgent challenges. Existing research has focused primarily on analyzing the characteristics of fake news and deepfakes as a function of a number of features, such as content, temporal patterns, and social network structure.

The overall challenge to be addressed in this project is the development of data analysis methodologies, with an emphasis on interpretable machine learning and network analysis to identify, analyze and mitigate the social effects of fake news and deepfakes in social networks. The core research of this project aims to answer the following research questions step-by-step.

How to characterize the features and diffusion patterns of fake news and deepfakes in social networks to detect possible influence and diffusion campaigns in specific contexts, e.g., anti-vaccine movements.
How to identify and assess the social effects of fake news and deepfakes in social networks in a systematic way with the use of data science and network analysis methods.
What intervention strategies can potentially be developed to overcome the negative social effects of fake news and deepfakes.
Eligibility criteria:

The potential impact and benefit of this project goes beyond its undoubted academic value; this innovative and exploratory research has the potential to support resilient security deterrence, effective intervention and policy branding in the fight against fake news and deepfakes, and mitigate their risk on individuals and society.

Application Procedure:

Yu-wang Chen [email protected],