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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Assessing Sentiment of the Expressed Stance on Social Media

verfasst von : Abeer Aldayel, Walid Magdy

Erschienen in: Social Informatics

Verlag: Springer International Publishing

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Abstract

Stance detection is the task of inferring viewpoint towards a given topic or entity either being supportive or opposing. One may express a viewpoint towards a topic by using positive or negative language. This paper examines how the stance is being expressed in social media according to the sentiment polarity. There has been a noticeable misconception of the similarity between the stance and sentiment when it comes to viewpoint discovery, where negative sentiment is assumed to mean against stance, and positive sentiment means in-favour stance. To analyze the relation between stance and sentiment, we construct a new dataset with four topics and examine how people express their viewpoint with regards these topics. We validate our results by carrying a further analysis of the popular stance benchmark SemEval stance dataset. Our analyses reveal that sentiment and stance are not highly aligned, and hence the simple sentiment polarity cannot be used solely to denote a stance toward a given topic.

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Vorheriges Kapitel Arabic Offensive Language Classification on Twitter
Nächstes Kapitel Do Events Change Opinions on Social Media? Studying the 2016 US Presidential Debates
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Metadaten
Titel
Assessing Sentiment of the Expressed Stance on Social Media
verfasst von
Abeer Aldayel
Walid Magdy
Copyright-Jahr
2019
Buch
Social Informatics

Print ISBN: 978-3-030-34970-7

Electronic ISBN: 978-3-030-34971-4

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-34971-4_19