Content Characteristics and Transmission Strategies of Social Media Rumors in China: Big Data Analysis of WeChat Rumors

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI:10.1109/BESC48373.2019.8963026

Lingnan He, Jing Gu, Dan Li, Kaisheng Lai

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引用次数: 1

Abstract

Understanding the characteristics and patterns of rumors on social media has become one of the key issues of rumor governance. However, there is some empirical evidence about the characteristics of rumors on WeChat, the most popular social media platform in China with more than 800 million users. To investigate the content characteristics and transmission strategies of rumors on WeChat, we collected 2175 rumor articles from WeChat from April 2015 to March 2016. It was found that political and societal rumors accounted for the highest proportion of rumors on WeChat. The proportion of positive emotional words found in the most popular rumors was significantly higher than that in the least popular rumors. Further analysis of rumor transmission strategies indicated that nearly one-third of the rumors have the interactive characteristics of induced sharing. Rumor articles on WeChat were mostly published around people's leisure time and holidays. Most articles were published in the front positions at each instance of time. However, the headline rumor articles did not receive the highest number of views and likes. Our findings can be beneficial for the scientific allocation of rumor regulatory resources and rumor intervention.

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中国社交媒体谣言的内容特征及传播策略——微信谣言的大数据分析

了解社交媒体谣言的特征和模式已成为谣言治理的关键问题之一。然而，有一些关于微信谣言特征的实证证据，微信是中国最受欢迎的社交媒体平台，拥有超过8亿用户。为了研究微信谣言的内容特征及传播策略，我们收集了2015年4月至2016年3月期间微信上的2175篇谣言文章。研究发现，政治和社会谣言在微信谣言中所占比例最高。在最流行的谣言中发现的积极情绪词的比例显著高于最不流行的谣言。对谣言传播策略的进一步分析表明，近三分之一的谣言具有诱导分享的互动特征。微信上的谣言文章大多是在人们的闲暇和假期发布的。大多数文章在每个时间点的前沿位置发表。然而，标题谣言文章的阅读量和点赞数并不是最高的。研究结果可为谣言监管资源的科学配置和谣言干预提供参考。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)

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