Understanding directional relationships on the platform is key to analyzing influence, information spread, and network dynamics. For example, if User A follows User B, User B’s tweets appear in User A’s timeline. This unidirectional link forms the basis of follower/following counts and contributes to the platform’s overall structure. Examining these connections allows for the identification of key influencers, the tracking of information cascades, and the study of community formation.
Analyzing these connections provides valuable insights for various applications. Marketers can identify influential accounts for targeted campaigns. Researchers can study the spread of misinformation or the formation of echo chambers. Journalists can track news dissemination and identify key sources. The historical development of this asymmetrical following model has shaped online social interaction, contributing to the platform’s distinct communication patterns and societal impact.
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