Stance Detection

Abstract

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 processing topic with diverse application areas, and our survey article on this newly emerging topic will act as a significant resource for interested researchers and practitioners.

Trends in combating fake news on social media – a survey

“…Fake detection takes several forms with some authors focusing on stance detection (Islam et al, 2019;Küçük & Can, 2020;Ma et al, 2018) this model tries to get the position of an individual whether he or she is for, against, or neutral in something. Detecting the position of someone is a fundamental step in knowing if such a person is for the truth or against it (Islam et al, 2019).…”

Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations

“…Previous datasets for stance detection have centered on two definitions of the task (Küçük and Can, 2020). In the most common definition (topicphrase stance), stance (pro, con, neutral) of a text is detected towards a topic that is usually a nounphrase (e.g., 'gun control').…”

Public Sentiment on Governmental COVID-19 Measures in Dutch Social Media

“…From a technical point of view, stance detection has recently received considerable attention in the NLP community (Küçük and Can, 2020), for which neural networks with word embeddings have proven to be effective (Yi-Chin Chen, 2017;Li and Caragea, 2019). An annotation and training approach for classifying hate speech in COVID-19 related tweets using embeddings was described by (Cotik et al, 2020).…”