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Stance Quantification: Definition of the Problem

arXiv 2112.13288 ↗First posted 25 Dec 2021cs.CLcited by 0

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Abstract (arXiv)

Stance detection is commonly defined as the automatic process of determining the positions of text producers, towards a target. In this paper, we define a research problem closely related to stance detection, namely, stance quantification, for the first time. We define stance quantification on a pair including (1) a set of natural language text items and (2) a target. At the end of the stance quantification process, a triple is obtained which consists of the percentages of the number of text items classified as Favor, Against, Neither, respectively, towards the target in the input pair. Also defined in the current paper is a significant subproblem of the stance quantification problem, namely, multi-target stance quantification. We believe that stance quantification at the aggregate level can lead to fruitful results in many application settings, and furthermore, stance quantification might be the sole stance related analysis alternative in settings where privacy concerns prevent researchers from applying generic stance detection.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 1 of its 5 references that are in the map. First posted on arXiv 25 Dec 2021.

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References · 1

  1. 2019Cross-Lingual Sentiment Quantificationcited by 2

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