Exploring the Relationship between User Posts and List Subscription Behaviors on Twitter/X

Social media platforms have transformed information consumption, offering personalized features that enhance engagement and streamline content discovery. Among these, the Twitter Lists functionality allows users to curate content by grouping accounts based on shared themes, fostering focused interactions and diverse perspectives. Despite their widespread use, the relationship between user-generated content and List subscription behaviors remains insufficiently explored. This study examines the alignment between users' post topics and their subscribed Lists, along with the influence of activity levels on this alignment. The role of content diversity in shaping subscription patterns to Lists covering a range of topics is also investigated. Additionally, the extent to which the affective characteristics—sentiment and emotion—of user posts correspond with the emotional tone of subscribed List content is analyzed. Utilizing a comprehensive Twitter dataset, advanced techniques for topic modeling, sentiment analysis, and emotion extraction were applied, and profiles for both users and Lists were developed to facilitate the exploration of their interrelationship. These insights advance the understanding of user interactions with Lists, informing the development of personalized recommendation systems and improved content curation strategies, with broad implications for social media research and platform functionality.

Keywords:

social network analysis , Twitter Lists , Behavioral patterns in List subscriptions