News announcement

【项目介绍】

Data Analytics for Addressing 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 societal effects. During the COVID-19 crisis, for example, the spread of various types of fake news through social media and social networks, has compromised the efficacy of non-pharmaceutical interventions and undermined the credibility of scientific evidence on vaccination. Identifying, analysing and mitigating the societal effects of fake news and deepfakes in social networks presents unique and urgent challenges. Existing research has focussed primarily on analysing the characteristics of fake news and deepfakes on a range of characteristics, such as content, temporal patterns and structure of social networks.

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

• How to characterise the features and spread patterns of fake news and deepfakes in social media in order to detect potential influence and dissemination campaigns in specific contexts, e.g., anti-vaccine movements.

• How to identify and evaluate the societal effects of fake news and deepfakes in social networks systematically with the use of data science and network analysis methods.

• What intervention strategies can potentially be developed to overcome the negative societal effects of fake news and deepfakes.

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 marking in fighting fake news and deepfakes, and mitigate their risk on individuals and society.

Project references: MN53

Application deadline: 9th April

项目链接：

【联系方式】

指导教授：Yu-wang Chen 

教授主页：https://www.research.manchester.ac.uk/portal/yu-wang.chen.html