{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:12:28Z","timestamp":1760195548216,"version":"build-2065373602"},"reference-count":75,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T00:00:00Z","timestamp":1519344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"GRRC program of Gyeonggi province","award":["2017-14-019"],"award-info":[{"award-number":["2017-14-019"]}]},{"name":"Japan Society for the Promotion of Science(JSPS)","award":["KAKENHI 15K15995"],"award-info":[{"award-number":["KAKENHI 15K15995"]}]},{"name":"New Energy and Industrial Technology Development Organization(NEDO)"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Analyses of social media have increased in importance for understanding human behaviors, interests, and opinions. Business intelligence based on social media can reduce the costs of managing customer trend complexities. This paper focuses on analyzing sensation information representing human perceptual experiences in social media through the five senses: sight, hearing, touch, smell, and taste. First a measurement is defined to estimate social sensation intensities, and subsequently sensation characteristics on geo-social media are identified using geo-spatial footprints. Finally, we evaluate the accuracy and F-measure of our approach by comparing with baselines.<\/jats:p>","DOI":"10.3390\/ijgi7020071","type":"journal-article","created":{"date-parts":[[2018,2,23]],"date-time":"2018-02-23T11:31:36Z","timestamp":1519385496000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Spatial Footprints of Human Perceptual Experience in Geo-Social Media"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"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, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7332-1778","authenticated-orcid":false,"given":"Hirotaka","family":"Ogawa","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"YongJin","family":"Kwon","sequence":"additional","affiliation":[{"name":"Department of Electronics and Information Engineering, Korea Aerospace University, Goyang-si, Gyeonggi-do 10540, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0670-8053","authenticated-orcid":false,"given":"Kyoung-Sook","family":"Kim","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Koto-ku, Tokyo 135-0064, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.bushor.2011.01.005","article-title":"Social media? 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