SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours

Genevieve Gorrell, E. Kochkina, Maria Liakata, Ahmet Aker, A. Zubiaga, Kalina Bontcheva, Leon Derczynski
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引用次数: 42

Abstract

Since the first RumourEval shared task in 2017, interest in automated claim validation has greatly increased, as the danger of “fake news” has become a mainstream concern. However automated support for rumour verification remains in its infancy. It is therefore important that a shared task in this area continues to provide a focus for effort, which is likely to increase. Rumour verification is characterised by the need to consider evolving conversations and news updates to reach a verdict on a rumour’s veracity. As in RumourEval 2017 we provided a dataset of dubious posts and ensuing conversations in social media, annotated both for stance and veracity. The social media rumours stem from a variety of breaking news stories and the dataset is expanded to include Reddit as well as new Twitter posts. There were two concrete tasks; rumour stance prediction and rumour verification, which we present in detail along with results achieved by participants. We received 22 system submissions (a 70% increase from RumourEval 2017) many of which used state-of-the-art methodology to tackle the challenges involved.
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SemEval-2019任务7:RumourEval,确定谣言的真实性和支持谣言
自2017年RumourEval首次共享任务以来,随着“假新闻”的危险成为主流担忧,人们对自动索赔验证的兴趣大大增加。然而,对谣言验证的自动化支持仍处于起步阶段。因此,重要的是,在这一领域的共同任务继续为可能增加的努力提供一个重点。谣言验证的特点是需要考虑不断发展的对话和新闻更新,以对谣言的真实性做出判断。与RumourEval 2017一样,我们提供了一个社交媒体上可疑帖子和随后对话的数据集,并对立场和真实性进行了注释。社交媒体上的谣言源于各种突发新闻故事,数据集扩展到包括Reddit和Twitter的新帖子。有两项具体任务;谣言立场预测和谣言验证,我们详细介绍了参与者取得的结果。我们收到了22份系统提交(比RumourEval 2017增加了70%),其中许多使用了最先进的方法来解决所涉及的挑战。
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