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      • Department of Computer Engineering
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      A tutorial on stance detection

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      Author(s)
      Küçük, Dilek
      Can, Fazlı
      Date
      2022
      Publisher
      Association for Computing Machinery, Inc
      Pages
      1626 - 1628
      Language
      English
      Type
      Conference Paper
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      Abstract
      Stance detection (also known as stance classification, stance prediction, and stance analysis) is a problem related to social media analysis, natural language processing, and information retrieval, which aims to determine the position of a person from a piece of text they produce, towards a target (a concept, idea, event, etc.) either explicitly specified in the text, or implied only. Common stance classes include Favor, Against, and None. In this tutorial, we will define the core concepts and other related research problems, present historical and contemporary approaches to stance detection (including shared tasks and tools employed), provide pointers to related datasets, and cover open research directions and application areas of stance detection. As solutions to stance detection can contribute to diverse applications including trend analysis, opinion surveys, user reviews, personalization, and predictions for referendums and elections, it will continue to stand as an important research problem, mostly on textual content currently, and particularly on Web content including social media.
      Keywords
      Stance detection
      Social media analysis
      Twitter
      Data streams
      Permalink
      http://hdl.handle.net/11693/111714
      Published Version (Please cite this version)
      https://dx.doi.org/10.1145/3488560.3501391
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      • Department of Computer Engineering 1561
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