Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media

Fuente: arXiv
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Main Authors: Katsios, Gregorios, Sa, Ning, Bhaumik, Ankita, Strzalkowski, Tomek
Format: Preprint
Published: 2024
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author Katsios, Gregorios
Sa, Ning
Bhaumik, Ankita
Strzalkowski, Tomek
author_facet Katsios, Gregorios
Sa, Ning
Bhaumik, Ankita
Strzalkowski, Tomek
contents The behavior and decision making of groups or communities can be dramatically influenced by individuals pushing particular agendas, e.g., to promote or disparage a person or an activity, to call for action, etc.. In the examination of online influence campaigns, particularly those related to important political and social events, scholars often concentrate on identifying the sources responsible for setting and controlling the agenda (e.g., public media). In this article we present a methodology for detecting specific instances of agenda control through social media where annotated data is limited or non-existent. By using a modest corpus of Twitter messages centered on the 2022 French Presidential Elections, we carry out a comprehensive evaluation of various approaches and techniques that can be applied to this problem. Our findings demonstrate that by treating the task as a textual entailment problem, it is possible to overcome the requirement for a large annotated training dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2405_00821
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media
Katsios, Gregorios
Sa, Ning
Bhaumik, Ankita
Strzalkowski, Tomek
Computation and Language
The behavior and decision making of groups or communities can be dramatically influenced by individuals pushing particular agendas, e.g., to promote or disparage a person or an activity, to call for action, etc.. In the examination of online influence campaigns, particularly those related to important political and social events, scholars often concentrate on identifying the sources responsible for setting and controlling the agenda (e.g., public media). In this article we present a methodology for detecting specific instances of agenda control through social media where annotated data is limited or non-existent. By using a modest corpus of Twitter messages centered on the 2022 French Presidential Elections, we carry out a comprehensive evaluation of various approaches and techniques that can be applied to this problem. Our findings demonstrate that by treating the task as a textual entailment problem, it is possible to overcome the requirement for a large annotated training dataset.
title Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media
topic Computation and Language
url https://arxiv.org/abs/2405.00821