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.

翻译：群体或社区的行为与决策可能受到推动特定议程的个体（例如，旨在推广或贬低某人或某活动、呼吁采取行动等）的显著影响。在考察在线影响力运动（尤其是与重大政治和社会事件相关的运动）时，学者们通常关注识别负责设定并控制议程的源头（例如公共媒体）。本文提出了一种方法，用于通过社交媒体检测具体的议程控制实例，尤其是在标注数据有限或缺失的情况下。我们利用围绕2022年法国总统选举的Twitter消息语料库，对可应用于此问题的多种方法和技术进行了全面评估。研究结果表明，通过将该任务视为文本蕴含问题，可以克服对大规模标注训练数据集的需求。