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Differentiating users by language and location estimation in sentiment analisys of informal text during major public events

机译:在重大公共活动期间对非正式文本进行情感分析时,通过语言和位置估计来区分用户

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摘要

In recent years there has been intense work on the analysis of social media to support marketing campaigns. A proper methodology for sentiment analysis is a crucial asset in this regard. However, when monitoring major public events the behaviour or social media users may be strongly biased by punctual actions of the participating characters and the sense of group belonging, which is typically linked to specific geographical areas. In this paper, we present a solution combining a location prediction methodology with an unsupervised technique for sentiment analysis to assess automatically the engagement of social network users in different countries during an event with worldwide impact. As far as the authors know, this is the first time such techniques are jointly considered. We demonstrate that the technique is coherent with the intrinsic disposition of individual users to typical actions of the characters participating in the events, as well as with the sense of group belonging. (C) 2018 Elsevier Ltd. All rights reserved.
机译:近年来,在分析社会媒体以支持营销活动方面进行了大量工作。在这方面,正确的情感分析方法是至关重要的资产。但是,在监视重大公共事件时,行为或社交媒体用户可能会由于参与角色的守时行为和群体归属感而受到严重偏见,而群体归属感通常与特定的地理区域相关。在本文中,我们提出了一种结合位置预测方法和无监督技术进行情感分析的解决方案,以自动评估社交网络用户在具有全球影响力的事件中在不同国家/地区的参与度。据作者所知,这是首次联合考虑此类技术。我们证明了该技术与单个用户对参与事件的角色的典型动作的固有倾向以及与群体归属感的一致性。 (C)2018 Elsevier Ltd.保留所有权利。

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