Interactional and Informational Attention on Twitter

Agathe Baltzer (1) , Márton Karsai (1, 2) , Camille Roth (3, 4)

1 DANTE - Dynamic Networks : Temporal and Structural Capture Approach
2 CEU - Central European University [Budapest, Hongrie]
3 CAMS - Centre d'Analyse et de Mathématique sociales
4 CMB - Centre Marc Bloch

Twitter may be considered to be a decentralized social information processing platform whose users constantly receive their followees’ information feeds, which they may in turn dispatch to their followers. This decentralization is not devoid of hierarchy and heterogeneity, both in terms of activity and attention. In particular, we appraise the distribution of attention at the collective and individual level, which exhibits the existence of attentional constraints and focus effects. We observe that most users usually concentrate their attention on a limited core of peers and topics, and discuss the relationship between interactional and informational attention processes—all of which, we suggest, may be useful to refine influence models by enabling the consideration of differential attention likelihood depending on users, their activity levels, and peers’ positions.

Domaines: Méthodes et statistiques; Sociologie; Informatique; Adaptation et Systèmes auto-organisés [nlin.AO]; Machine Learning [stat.ML]

Agathe Baltzer, Márton Karsai, Camille Roth. Interactional and Informational Attention on Twitter. Information, 2019, 10 (8), pp.1-16. ⟨10.3390/info10080250⟩. ⟨halshs-02378190⟩