Project: Analysis of Online Social Media Networks

Project topic: Analysis of Online Social Media Networks

This research project aims to explore new methods for quantitative measurements and models of users behaviour on online social media networks, such as X (formerly known as Twitter). 

A wide range of scientific methods can be utilised, including machine learning methods (such as decision tree models, feature importance analysis, neural network models, neural embedding etc.), statistical/computing methods (such as Bayesian inference, dimension deduction algorithms and numerical simulations), and network science methods (such as network community detection and PageRank).  

Research questions:

1). How to predict the probability of a user reposting a message posted by another user? While most existing methods focused on analysing the content of message, our experimental results suggest that a significant component of reposting behaviour can be predicted based on users' profile and past behaviour, and is independent of the content of messages. 

2). How to measure a user' opinion based solely on its social connections with other users?  

• BSc project thesis (2024) Title: Opinion Measurement Based on Social Connectivity Data 

• MSc project thesis (2024) Title: Ideological positioning of US Congress members using Twitter following networks

Requirements: 

• Good knowledge and skills in mathematics and machine learning. Knowledge on network science is a bonus. 

• Good skills and experience in programming, such as Python.

Contact:

Please contact Shi ZHOU <s.zhou (at) ucl.ac.uk> for more information.