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Discovering underlying sensations of human emotions based on social media

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  • Jun Lee
  • Adam Jatowt
  • Kyoung‐Sook Kim

Abstract

Analyzing social media has become a common way for capturing and understanding people's opinions, sentiments, interests, and reactions to ongoing events. Social media has thus become a rich and real‐time source for various kinds of public opinion and sentiment studies. According to psychology and neuroscience, human emotions are known to be strongly dependent on sensory perceptions. Although sensation is the most fundamental antecedent of human emotions, prior works have not looked into their relation to emotions based on social media texts. In this paper, we report the results of our study on sensation effects that underlie human emotions as revealed in social media. We focus on the key five types of sensations: sight, hearing, touch, smell, and taste. We first establish a correlation between emotion and sensation in terms of linguistic expressions. Then, in the second part of the paper, we define novel features useful for extracting sensation information from social media. Finally, we design a method to classify texts into ones associated with different types of sensations. The sensation dataset resulting from this research is opened to the public to foster further studies.

Suggested Citation

  • Jun Lee & Adam Jatowt & Kyoung‐Sook Kim, 2021. "Discovering underlying sensations of human emotions based on social media," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 417-432, April.
    • Handle: RePEc:bla:jinfst:v:72:y:2021:i:4:p:417-432
    DOI: 10.1002/asi.24414
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    References listed on IDEAS

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    4. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
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