@inproceedings{sartori-etal-2025-insights,
    title = "Insights into using temporal coordinated behaviour to explore connections between social media posts and influence",
    author = "Sartori, Elisa  and
      Tardelli, Serena  and
      Tesconi, Maurizio  and
      Conti, Mauro  and
      Galeazzi, Alessandro  and
      Cresci, Stefano  and
      Da San Martino, Giovanni",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.1325/",
    doi = "10.18653/v1/2025.findings-emnlp.1325",
    pages = "24392--24404",
    ISBN = "979-8-89176-335-7",
    abstract = "Political campaigns increasingly rely on targeted strategies to influence voters on social media. Often, such campaigns have been studied by analysing coordinated behaviour to identify communities of users who exhibit similar patterns. While these analyses are typically conducted on static networks, recent extensions to temporal networks allow tracking users who change communities over time, opening new opportunities to quantitatively study influence in social networks. As a first step toward this goal, we analyse the messages users were exposed to during the UK 2019 election, comparing those received by users who shifted communities with others covering the same topics.Our findings reveal 54 statistically significant linguistic differences and show that a subset of persuasion techniques, including loaded language, exaggeration and minimization, doubt, and flag-waving, are particularly relevant to users' shifts. This work underscores the importance of analysing coordination from a temporal and dynamic perspective to infer the drivers of users' shifts in online debate."
}