Analysing Controversy on Twitter via Graph Embeddings

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http://urn.fi/URN:NBN:fi:hulib-202009294150
Title: Analysing Controversy on Twitter via Graph Embeddings
Author: Comănescu, Andrei-Daniel
Contributor: University of Helsinki, Faculty of Science
Publisher: Helsingin yliopisto
Date: 2020
URI: http://urn.fi/URN:NBN:fi:hulib-202009294150
http://hdl.handle.net/10138/319784
Thesis level: master's thesis
Abstract: Social networks represent a public forum of discussion for various topics, some of them controversial. Twitter is such a social network; it acts as a public space where discourse occurs. In recent years the role of social networks in information spreading has increased. As have the fears regarding the increasingly polarised discourse on social networks, caused by the tendency of users to avoid exposure to opposing opinions, while increasingly interacting with only like-minded individuals. This work looks at controversial topics on Twitter, over a long period of time, through the prism of political polarisation. We use the daily interactions, and the underlying structure of the whole conversation, to create daily graphs that are then used to obtain daily graph embeddings. We estimate the political ideologies of the users that are represented in the graph embeddings. By using the political ideologies of users and the daily graph embeddings, we offer a series of methods that allow us to detect and analyse changes in the political polarisation of the conversation. This enables us to conclude that, during our analysed time period, the overall polarisation levels for our examined controversial topics have stagnated. We also explore the effects of topic-related controversial events on the conversation, thus revealing their short-term effect on the conversation as a whole. Additionally, the linkage between increased interest in a topic and the increase of political polarisation is explored. Our findings reveal that as the interest in the controversial topic increases, so does the political polarisation.
Subject: graph embedding
social networks
graphs
controversy analysis
Discipline: none


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