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Predicting Online Protest Participation of Social Media Users

机译:预测在线抗议社交媒体用户参与

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Social media has emerged to be a popular platform for people to express their viewpoints on political protests like the Arab Spring. Millions of people use social media to communicate and mobilize their viewpoints on protests. Hence, it is a valuable tool for organizing social movements. However, the mechanisms by which protest affects the population is not known, making it difficult to estimate the number of protestors. In this paper, we are inspired by sociological theories of protest participation and propose a framework to predict from the user's past status messages and interactions whether the next post of the user will be a declaration of protest. Drawing concepts from these theories, we model the interplay between the user's status messages and messages interacting with him over time and predict whether the next post of the user will be a declaration of protest. We evaluate the framework using data from the social media platform Twitter on protests during the recent Nigerian elections and demonstrate that it can effectively predict whether the next post of a user is a declaration of protest.
机译:社交媒体已经成为一个受欢迎的人们对人们表示对阿拉伯春天等政治抗议的观点。数百万人使用社交媒体来沟通和动员他们对抗议观点的观点。因此,它是组织社会运动的宝贵工具。然而,抗议影响人口的机制尚不清楚,使得难以估计抗议者的数量。在本文中,我们受到抗议参与的社会学理论的启发,并提出了一个框架,以预测用户过去的状态消息和交互,无论用户的下一篇文章是否都是抗议声明。从这些理论中绘制概念,我们模拟了用户的状态消息与消息与他交互的消息之间的相互作用,并预测用户的下一个帖子是否是抗议声明。我们在最近的尼日利亚选举中使用来自社交媒体平台推特上的数据的数据评估框架,并证明它可以有效预测用户的下一个帖子是否是抗议声明。

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