Assessing Sentiment of the Expressed Stance on Social Media

Abeer Aldayel, Walid Magdy

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.
Original languageEnglish
Title of host publicationSocial Informatics
Subtitle of host publication11th International Conference, SocInfo 2019
PublisherSpringer, Cham
Number of pages9
ISBN (Electronic)978-3-030-34971-4
ISBN (Print)978-3-030-34970-7
Publication statusPublished - 11 Nov 2019
Event11th International Conference on Social Informatics - Doha, Qatar
Duration: 18 Nov 201921 Nov 2019

Publication series

NameLecture Notes in Computer Sciences (LNCS)
PublisherSpringer, Cham
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Social Informatics
Abbreviated titleSocInfo 2019
Internet address


  • Stance detection
  • Sentiment analysis
  • Public opinion
  • Event analysis
  • Social media

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