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Can I read Stance Detection: A Survey on EtoBox?
Stance Detection: A Survey by Dilek Küçük; Fazli Can is a Computer Science article available to read on EtoBox.
What is Stance Detection: A Survey about?
Automatic elicitation of semantic information from natural language texts is an important research problem with many practical application areas. Especially after the recent proliferation of online content through channels such as social media sites, news portals, and forums; solutions to problems such as sentiment analysis, sarcasm/controversy/veracity/rumour/fake news detection, and argument mining gained increasing impact and significance, revealed with large volumes of related scientific publications. In this article, we tackle an important problem from the same family and present a survey of stance detection in social media posts and (online) regular texts. Although stance detection is defined in different ways in different application settings, the most common definition is “automatic classification of the stance of the producer of a piece of text, towards a target, into one of these three classes: { Favor , Against , Neither }.” Our survey includes definitions of related problems and concepts, classifications of the proposed approaches so far, descriptions of the relevant datasets and tools, and related outstanding issues. Stance detection is a recent natural language proces
Who reads Stance Detection: A Survey?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Dilek Küçük; Fazli Can
- Publisher
- ACM
- Published
- 2020
- Language
- EN
- Field
- Computer Science (Physical Sciences)