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Automatically Identifying Complaints in Social Media

机译:自动识别社交媒体的投诉

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Complaining is a basic speech act regularly used in human and computer mediated communication to express a negative mismatch between reality and expectations in a particular situation. Automatically identifying complaints in social media is of utmost importance for organizations or brands to improve the customer experience or in developing dialogue systems for handling and responding to complaints. In this paper, we introduce the first systematic analysis of complaints in computational linguistics. We collect a new annotated data set of written complaints expressed in English on Twitter.~1 We present an extensive linguistic analysis of complaining as a speech act in social media and train strong feature-based and neural models of complaints across nine domains achieving a predictive performance of up to 79 F1 using distant supervision.
机译:抱怨是人类和计算机导明的沟通的基本言语行为,以特定情况表达现实与期望之间的负面不匹配。自动识别社交媒体的投诉对于改善客户体验或制定对话制度进行处理和应对投诉的对话系统至关重要。在本文中,我们介绍了对计算语言学投诉的第一个系统分析。我们在Twitter上收集新的注释数据集的书面投诉。〜1我们在社交媒体和培训了九个域名的呼吸致辞和培训九个域名的讲话法案的广泛语言学分析,以实现预测的九个域名的讲话和培训的强大和神经模型。使用遥远监督最多可达79 F1。

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