Analysing Conspiracy Theories on Social and Online Media [Multiple Projects]

Brandon Davies


Supervised by Alun D Preece; Moderated by Nervo Verdezoto Dias

The damage misinformation and conspiracy theories can cause has risen to prominence in recent years. During the COVID-19 pandemic, conspiracy theories spread via social media have led to numerous disruptive events including attacks on 5G towers and direct action by anti-vaccination groups. In the political arena, QAnon conspiracy theorists were involved in the January 2021 attack on the United States Capitol, threatening the legitimate democratic process of a major nation state.

This project is centred around the analysis of conspiracy theories on online media and will involve: -- The collection of social media (e.g. Twitter) and/or online news media data -- The use of text analytics and natural language processing (NLP) to interrogate the data -- The use of data visualisation techniques -- [ADVANCED] Application of predictive analytics to anticipate the direction of a given conspiracy or movement

The primary aim of the project is to characterise conspiracy theories in social and/or online news media. News media and Twitter datasets will be made available but the collection of new data is strongly encouraged.

This project is suitable for students who have studied machine learning and NLP; however, the topic is also open to conversion MSc students who have a keen interest in the subject of conspiracy theories and a willingness to learn NLP/text analytics methods.

Final Report (21/09/2022) [Zip Archive]

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