Küçük, DilekCan, Fazlı2022-02-092022-02-092021-07-11978-1-4503-8037-9http://hdl.handle.net/11693/77159Conference Name: SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information RetrievalDate of Conference: 11-15 July 2021Stance detection (also known as stance classification and stance prediction) is a problem related to social media analysis, natural language processing, and information retrieval, which aims to de termine the position of a person from a piece of text they produce, towards a target (a concept, idea, event, etc.) either explicitly speci fied in the text, or implied only. The output of the stance detection procedure is usually from this set: {Favor, Against, None}. In this tutorial, we will define the core concepts and research problems re lated to stance detection, present historical and contemporary ap proaches to stance detection, provide pointers to related resources (datasets and tools), and we will cover outstanding issues and ap plication areas of stance detection. As solutions to stance detection can contribute to significant tasks including trend analysis, opin ion surveys, user reviews, personalization, and predictions for ref erendums and elections, it will continue to stand as an important research problem, mostly on textual content currently, and partic ularly on social media. Finally, we believe that image and video content will commonly be the subject of stance detection research soon.EnglishStance detectionSocial media analysisDeep learningData streamsConference Paper10.1145/3404835.3462815