Techniques for Agenda Detection

Anonymous

Abstract: The behavior and decision making of groups or communities can be dramatically influenced by individuals pushing particular agendas. 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 the agenda (e.g., public media). In this article we present a methodology for detecting specific instances of agendas in situations 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 of text classification as a textual entailment problem, it is possible to overcome the requirement for a large annotated dataset.

Paper Type: long

Research Area: Semantics: Sentence-level Semantics, Textual Inference and Other areas