Can nationalistic information spread like virus?: A cascade tree analysis of diffusion pattern on WeChat moments

2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC) Pub Date : 2017-10-01 DOI:10.1109/BESC.2017.8256400

Lingnan He, Hao-Yu Yang, Zhiwei Lin, Kaisheng Lai, Zhi'an Zhang

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引用次数: 1

Abstract

WeChat Moments has become an important way for Chinese people to access the latest news. And nationalistic sentiment seems to make some news spread very quickly and get a lot for people involved in, i.e. a viruses-like communication pattern. Is this true? In this study, by constructing cascade trees, we analyzed the diffusion patterns of 175 HTML5 web pages with a complete lifecycle on WeChat Moment during July, 2016. Each page was viewed by more than 10,000 users, and more than two hundred million users are involved in the spread of these pages in total. Results indicated that pages arousing nationalistic sentiment spread more rapidly, attract more sharing behavior, diffuse more like a virus and have a shorter lifespan than other kind of popular pages. Furthermore, this diffusion pattern depends on the credibility of information. Only for the information of high credibility, pages with nationalistic information tend to have deeper cascade trees, higher sharing ratio and spread faster.

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民族主义信息会像病毒一样传播吗?:微信朋友圈扩散模式的级联树分析

微信朋友圈已经成为中国人获取最新消息的重要方式。民族主义情绪似乎使一些新闻传播得很快，并为参与其中的人带来很多好处，即一种类似病毒的传播模式。这是真的吗?本研究通过构建级联树，分析了2016年7月175个具有完整生命周期的HTML5网页在微信朋友圈的传播模式。每个页面都有超过1万名用户浏览，这些页面的传播总共有超过2亿用户参与。结果表明，与其他类型的热门页面相比，煽动民族主义情绪的页面传播速度更快，吸引更多的分享行为，传播更像病毒，寿命更短。此外，这种传播模式取决于信息的可信度。只有对于高可信度的信息，具有民族主义信息的页面往往具有更深的级联树，更高的分享率，传播速度更快。

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2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)

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