人气
万维网
社会化媒体
用户参与度
排名(信息检索)
计算机科学
互联网隐私
网页
Altmetrics公司
情报检索
心理学
社会心理学
作者
Andrea Zaccaria,Michela Del Vicario,Walter Quattrociocchi,Antonio Scala,L. Pietronero
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2019-01-28
卷期号:14 (1): e0211038-e0211038
被引量:12
标识
DOI:10.1371/journal.pone.0211038
摘要
The advent of social networks revolutionized the way people access to information sources. Understanding the complex relationship between these sources and users is crucial. We introduce an algorithm, that we call PopRank, to assess both the Impact of Facebook pages as well as users' Engagement on the basis of their mutual interactions. The ideas behind the PopRank are that i) high impact pages attract many users with a low engagement, which means that they receive comments from users that rarely comment, and ii) high engagement users interact with high impact pages, that is they mostly comment pages with a high popularity. The resulting ranking of pages can predict the number of comments a page will receive and the number of its future posts. Pages' impact turns out to be slightly dependent on the quality of pages' informative content (e.g., science vs conspiracy) but independent of users' polarization.
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