ArticlePloS one2017
Users' participation and social influence during information spreading on Twitter.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Spreading predictability in complex networks.Scientific reports · 2021Article
- Influence Cascades: Entropy-Based Characterization of Behavioral Influence Patterns in Social Media.Entropy (Basel, Switzerland) · 2021Article
- Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure.Journal of medical Internet research · 2018Article
- Article
- The Why We Retweet scale.PloS one · 2018Article
- Multi-criteria decision support for planning and evaluation of performance of viral marketing campaigns in social networks.PloS one · 2018Article
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Authors and funding
4 authors.
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Abstract
Online Social Networks generate a prodigious wealth of real-time information at an incessant rate. In this paper we study the empirical data that crawled from Twitter to describe the topology and information spreading dynamics of Online Social Networks. We propose a measurement with three measures to state the efforts of users on Twitter to get their information spreading, based on the unique mechanisms for information retransmission on Twitter. It is noticed that small fraction of users with special performance on participation can gain great influence, while most other users play a role as middleware during the information propagation. Thus a community analysis is performed and four categories of users are found with different kinds of participation that cause the information dissemination dynamics. These suggest that exiting topological measures alone may reflect little about the influence of individuals and provide new insights for information spreading.
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