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Interactional and Informational Attention on Twitter

1,2,†, 1,*,† and 3,*,†
1
Univ Lyon, Inria, CNRS, ENS de Lyon, Université Claude Bernard Lyon 1, LIP UMR 5668, F-69007 Lyon, France
2
Mines ParisTech, 75006 Paris, France
3
CNRS and Computational Social Science Team, Centre Marc Bloch, UMIFRE CNRS-MAEE 14, Friedrichstrasse 191, D-10117 Berlin, Germany
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Information 2019, 10(8), 250; https://doi.org/10.3390/info10080250
Received: 24 May 2019 / Revised: 5 July 2019 / Accepted: 24 July 2019 / Published: 29 July 2019
(This article belongs to the Special Issue Computational Social Science)
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Abstract

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. View Full-Text
Keywords: attention; influence; ego-centered networks; twitter study; information spreading attention; influence; ego-centered networks; twitter study; information spreading
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Baltzer, A.; Karsai, M.; Roth, C. Interactional and Informational Attention on Twitter. Information 2019, 10, 250.

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