Insights into using temporal coordinated behaviour to explore connections between social media posts and influence

ACL ARR 2025 May Submission7104 Authors

Abstract:

Political campaigns make increasing use of targeted strategies to influence %and coordinate
voters on social media.
The analysis of coordinated behaviour allows to determine communities of users that exhibit the same patterns of behaviours. While such analysis is generally performed on static networks, recent extensions to the temporal dimension allowed to highlight users that changed community over time.
This may open up new possibilities to quantitatively study influence in social networks. As a first step towards that goal,
we set out to analyze the messages users are exposed to and comparing users that changed community with the rest.
Our findings show $54$ statistically significant linguistic differences and analyses the effectiveness of the use of persuasion techniques, showing that few of them, i.e. loaded language, exaggeration and minimisation, doubt and flag-waving seem to be the most effective for the dataset we studied, tweets on the UK 2019 elections.

Paper Type: Long

Research Area: Computational Social Science and Cultural Analytics

Research Area Keywords: Computational Social Science and Cultural Analytics

Contribution Types: Data analysis

Languages Studied: English

Submission Number: 7104