Name
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/info10080250 | INFORMATION |
Keywords | Field | DocType |
attention, influence, ego-centered networks, twitter study, information spreading | Data science,Decentralization,Computer science,Social information processing,Artificial intelligence,Hierarchy,Machine learning | Journal |
Volume | Issue | Citations |
10 | 8 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Agathe Baltzer | 1 | 0 | 0.34 |
| Márton Karsai | 2 | 422 | 30.42 |
| Camille Roth | 3 | 0 | 0.34 |