衡量推特上阿拉伯语热门话题的争议程度

Abdullateef Rabab'ah, M. Al-Ayyoub, Y. Jararweh, M. Al-Kabi
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引用次数: 10

摘要

像推特这样的社交微博系统如今被用作一个平台,让用户可以写下不同的话题。这种人际互动的一个重要方面是存在辩论和分歧。最激烈的辩论发生在有争议的话题上。检测这些主题对于理解在线社交网络用户的行为和他们互动的动态是非常有益的。这样的理解会带来更好的方法来处理和预测“在线人群”的行为。人们提出了几种方法来检测在线交流中的争议。他们中的一些人以图的形式表示相互作用,并研究它们的性质,以确定相互作用的话题是否有争议。其他方法依赖于交换消息的内容。在本研究中,我们将重点放在前一种方法上,以确定Twitter上热门话题的争议程度。与之前的许多作品不同,我们没有将自己限制在某个领域。此外,我们专注于用阿拉伯语撰写的有关中东热点事件的社会内容。据我们所知,我们的工作是第一次采用这种方法来研究用阿拉伯语写的一般主题的争议。我们收集了来自不同领域的不同热门话题的大量tweets数据集。我们应用了几种争议检测方法,并比较了它们的结果,以确定哪一种是最一致的测量方法。
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Measuring the controversy level of Arabic trending topics on Twitter
Social micro-blogging systems like Twitter are used today as a platform that enables its users to write down about different topics. One important aspect of such human interactions is the existence of debate and disagreement. The most heated debates are found on controversial topics. Detecting such topics can be very beneficial in understanding the behavior of online social networks users and the dynamics of their interactions. Such an understanding leads to better ways of handling and predicting how the "online crowds" will act. Several approaches have been proposed for detecting controversy in online communication. Some of them represent the interactions in the form of graphs and study their properties in order to determine whether the topic of interaction is controversial or not. Other approaches rely on the content of the exchanged messages. In this study, we focus on the former approach in identifying the controversy level of the trending topics on Twitter. Unlike many previous works, we do not limit ourselves to a certain domain. Moreover, we focus on social content written in Arabic about hot events occurring in the Middle East. To the best of our knowledge, ours is the first work to undertake this approach in studying controversy in general topics written in Arabic. We collect a large dataset of tweets on different trending topics from different domains. We apply several approaches for controversy detection and compare their outcomes to determine which one is the most consistent measure.
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