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Automated Detection of Nostalgic Text in the Context of Societal Pessimism

机译:在社会悲观主义背景下自动检测怀旧文本

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In online media environments, nostalgia can be used as important ingredient of propaganda strategies, specifically, by creating societal pessimism. This work addresses the automated detection of nostalgic text as a first step towards automatically identifying nostalgia-based manipulation strategies. We compare the performance of standard machine learning approaches on this challenge and demonstrate the successful transfer of the best performing approach to real-world nostalgia detection in a case study.
机译:在在线媒体环境中,Nostalgia可以用作宣传策略的重要成分,具体而言,通过创造社会悲观主义。这项工作解决了Nostalgic文本的自动检测作为自动识别基于怀旧的操纵策略的第一步。我们比较标准机器学习方法对这一挑战的表现,并证明了在案例研究中成功转移现实世界怀旧检测的最佳表现方法。

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