Finding polarised communities and tracking information diffusion on Twitter: The Irish Abortion Referendum

Fuente: arXiv
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Autores principales: Pena, Caroline, MacCarron, Pádraig, O'Sullivan, David J. P.
Formato: Preprint
Publicado: 2023
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author Pena, Caroline
MacCarron, Pádraig
O'Sullivan, David J. P.
author_facet Pena, Caroline
MacCarron, Pádraig
O'Sullivan, David J. P.
contents The analysis of social networks enables the understanding of social interactions, polarisation of ideas, and the spread of information and therefore plays an important role in society. We use Twitter data - as it is a popular venue for the expression of opinion and dissemination of information - to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarised climate. To achieve this, we collected over 688,000 Tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users mentions with sentiment-based homophily. From this network, community detection methods allow us to isolate yes- or no-aligned supporters with high accuracy (90.9%). We supplement this by tracking how information cascades spread via over 31,000 retweet-cascades. We found that very little information spread between polarised communities. This provides a valuable methodology for extracting and studying information diffusion on large networks by isolating ideologically polarised groups and exploring the propagation of information within and between these groups.
format Preprint
id arxiv_https___arxiv_org_abs_2311_09196
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Finding polarised communities and tracking information diffusion on Twitter: The Irish Abortion Referendum
Pena, Caroline
MacCarron, Pádraig
O'Sullivan, David J. P.
Social and Information Networks
The analysis of social networks enables the understanding of social interactions, polarisation of ideas, and the spread of information and therefore plays an important role in society. We use Twitter data - as it is a popular venue for the expression of opinion and dissemination of information - to identify opposing sides of a debate and, importantly, to observe how information spreads between these groups in our current polarised climate. To achieve this, we collected over 688,000 Tweets from the Irish Abortion Referendum of 2018 to build a conversation network from users mentions with sentiment-based homophily. From this network, community detection methods allow us to isolate yes- or no-aligned supporters with high accuracy (90.9%). We supplement this by tracking how information cascades spread via over 31,000 retweet-cascades. We found that very little information spread between polarised communities. This provides a valuable methodology for extracting and studying information diffusion on large networks by isolating ideologically polarised groups and exploring the propagation of information within and between these groups.
title Finding polarised communities and tracking information diffusion on Twitter: The Irish Abortion Referendum
topic Social and Information Networks
url https://arxiv.org/abs/2311.09196