Stance detection: concepts, approaches, resources, and outstanding issues

buir.contributor.authorCan, Fazlı
dc.citation.epage2676en_US
dc.citation.spage2673en_US
dc.contributor.authorKüçük, Dilek
dc.contributor.authorCan, Fazlı
dc.coverage.spatialNew York, NY, United Statesen_US
dc.date.accessioned2022-02-09T09:31:08Z
dc.date.available2022-02-09T09:31:08Z
dc.date.issued2021-07-11
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionConference Name: SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrievalen_US
dc.descriptionDate of Conference: 11-15 July 2021en_US
dc.description.abstractStance 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.en_US
dc.identifier.doi10.1145/3404835.3462815en_US
dc.identifier.isbn978-1-4503-8037-9en_US
dc.identifier.urihttp://hdl.handle.net/11693/77159en_US
dc.language.isoEnglishen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofhttps://dx.doi.org/10.1145/3404835.3462815en_US
dc.source.titleSIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrievalen_US
dc.subjectStance detectionen_US
dc.subjectSocial media analysisen_US
dc.subjectDeep learningen_US
dc.subjectData streamsen_US
dc.titleStance detection: concepts, approaches, resources, and outstanding issuesen_US
dc.typeConference Paperen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Stance_detection_concepts,_approaches,_resources,_and_outstanding_issues.pdf
Size:
1.03 MB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.69 KB
Format:
Item-specific license agreed upon to submission
Description: