  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.
