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Social media has thus become a rich and real\u2010time 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.<\/jats:p>","DOI":"10.1002\/asi.24414","type":"journal-article","created":{"date-parts":[[2020,9,30]],"date-time":"2020-09-30T02:19:46Z","timestamp":1601432386000},"page":"417-432","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Discovering underlying sensations of human emotions based on social media"],"prefix":"10.1002","volume":"72","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-6138-3971","authenticated-orcid":false,"given":"Jun","family":"Lee","sequence":"first","affiliation":[{"name":"Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology (AIST)  Tokyo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Jatowt","sequence":"additional","affiliation":[{"name":"Graduate School of Informatics Kyoto University  Kyoto Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyoung\u2010Sook","family":"Kim","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology (AIST)  Tokyo Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,9,29]]},"reference":[{"key":"e_1_2_7_2_1","unstructured":"Baccianella S. 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