Project Abstract

The spread of misinformation through social media has led to significant issues in sectors like public health and political discourse. We leverage Twitter data to create misinformation models using agent-based models. We aim to understand the spreading pattern of misinformation and the human response to it. This research will also create intervention mechanisms that will combat the spreading of fake news and its impact on the population.

Project Description & Overview

The pervasiveness and accessibility of social media across vast networks of people have rendered it a prime target for spreading malicious misinformation. Historically, social bots have often been deployed targeting certain groups of people in a social network, often with a political agenda. The recent spread of the coronavirus pandemic has also suffered from the spread of harmful and misinformed health-related news. This project aims to use agent-based modeling to model the spread of misinformation in a social network, and couple the spread of misinformation with the spread of a real-world disease. The project aims to use Twitter data to create a heterogeneous network to replicate a real social network by accounting for varying node centrality and creating connections based on shared geographical, political, or general interest attributes. This research will deploy social bots that constantly spread misinformation in the network. We will study the vulnerabilities of the agents based on the agent’s political biases, trust with the agent sharing the misinformation, as well as previous experiences with getting misinformed. We aim to understand how the misinformed agents respond to health-related misinformation and predict the impact of fake news in the real world.

Datasets

There are many online Twitter datasets that can be used for this research. The students can also collect their own datasets from Twitter.

Competencies

The students should have fundamental programming skills and interest in system modeling and research.

Learning Outcomes & Deliverables 

1. Create agent-based models based on datasets.
2. Analyze the pattern of spreading.
3. Create methods to combat fake news and its spreading.

Students

Jiaming Chen, Tong Cui, Jiayuan Huang, Wengan Xiao