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Diffusion of pro- and anti-false information tweets: the Black Panther movie case
Computational and Mathematical Organization Theory ( IF 1.8 ) Pub Date : 2018-11-21 , DOI: 10.1007/s10588-018-09286-x
Matthew Babcock , Ramon Alfonso Villa Cox , Sumeet Kumar

Much has been made of the importance of the speed at which disinformation diffuses through online social media and this speed is an important aspect to consider when designing interventions. An additional complexity is that there can be different types of false information that travel from and through different communities who respond in various ways within the same social media conversation. Here we present a case study/example analysis exploring the speed and reach of three different types of false stories found in the Black Panther movie Twitter conversation and comparing the diffusion of these stories with the community responses to them. We find that the negative reaction to fake stories of racially-motivated violence whether in the form of debunking quotes or satirical posts can spread at speeds that are magnitudes higher than the original fake stories. Satire posts, while less viral than debunking quotes, appear to have longer lifetimes in the conversation. We also found that the majority of mixed community members who originally spread fake stories switched to attacking them. Our work serves as an example of the importance of analyzing the diffusion of both different types of disinformation and the different responses to it within the same overall conversation.

中文翻译:

赞成和反对虚假信息鸣叫的扩散:“黑豹”电影案

通过网络社交媒体传播虚假信息的速度非常重要,这种速度是设计干预措施时要考虑的重要方面。另一个复杂性是,可能存在来自和通过不同社区传播的不同类型的虚假信息,这些社区在同一社交媒体对话中以各种方式做出响应。在这里,我们提供一个案例研究/示例分析,探讨在“黑豹”电影Twitter对话中发现的三种不同类型的虚假故事的速度和影响范围,并将这些故事的传播与社区对它们的回应进行比较。我们发现,对以种族为动机的暴力的假故事的负面反应,无论是以揭穿行情还是讽刺文章的形式传播,其传播速度都比原始假故事高出许多。讽刺帖子虽然不如揭穿行情那样具有病毒性,但它们在对话中的寿命似乎更长。我们还发现,最初散布假故事的大多数混合社区成员都转而攻击他们。我们的工作作为一个例子,说明了在同一整体对话中分析两种类型的虚假信息的传播以及对它的不同响应的重要性。我们还发现,最初散布假故事的大多数混合社区成员都转而攻击他们。我们的工作作为一个例子,说明了在同一整体对话中分析两种类型的虚假信息的传播以及对它的不同响应的重要性。我们还发现,最初散布假故事的大多数混合社区成员都转而攻击他们。我们的工作作为一个例子,说明了在同一整体对话中分析两种类型的虚假信息的传播以及对它的不同响应的重要性。
更新日期:2018-11-21
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