{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:18:09Z","timestamp":1750306689754,"version":"3.41.0"},"reference-count":5,"publisher":"Association for Computing Machinery (ACM)","issue":"Spring","license":[{"start":{"date-parts":[[2014,4,1]],"date-time":"2014-04-01T00:00:00Z","timestamp":1396310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGWEB Newsl."],"published-print":{"date-parts":[[2014,4]]},"abstract":"<jats:p>Geo-social media represents geo-tagged crowd-sourced media emerged from the wide-spread dissemination of smartphones and the availability of social media during daily social activities. Nowadays, with such novel media as a fertile ground to observe a variety of social phenomena, we can explore geo-social knowledge with the unprecedented scale of crowd lifelogs. In this article, we will overview our pioneering work that has been conducted to explore and exploit geo-social knowledge utilizing geo-tagged twitter data. In our study, we established a model to look into crowd behavior and mental status that are observed from local twitter data. Based on our novel perspective to examine the macro-scale crowd lifestyle patterns, we attempted to explore and exploit three types of geo-social knowledge; local event detectio , urban area characterization, and crowd sense of distance in urban space. In the conclusion, we will summarize our contribution to take advantages of the explosively growing geo-social media and briefly describe our future direction.<\/jats:p>","DOI":"10.1145\/2591453.2591457","type":"journal-article","created":{"date-parts":[[2014,4,1]],"date-time":"2014-04-01T13:06:54Z","timestamp":1396357614000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["\"Geo-social media analytics: exploring and exploiting geo-social experience from crowd-sourced lifelogs\" by R. Lee, S. Wakamiya, and K. Sumiya with Ching-man Au Yeung as coordinator"],"prefix":"10.1145","volume":"2014","author":[{"given":"Ryong","family":"Lee","sequence":"first","affiliation":[{"name":"Korea Institute of Science and Technology Informtion (KISTI), Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shoko","family":"Wakamiya","sequence":"additional","affiliation":[{"name":"Kyoto Sangyo University, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazutoshi","family":"Sumiya","sequence":"additional","affiliation":[{"name":"University of Hyogo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,4]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Alan Mislove Sune Lehmann Yong-Yeol Ahn Jukka-Pekka Onnela J. Niels Rosenquist: Pulse of the nation: US mood throughout the day inferred from twitter. http:\/\/www.ccs. neu.edu\/home\/amislove\/twittermood\/ (Accessed February 28 2014)  Alan Mislove Sune Lehmann Yong-Yeol Ahn Jukka-Pekka Onnela J. Niels Rosenquist: Pulse of the nation: US mood throughout the day inferred from twitter. http:\/\/www.ccs. neu.edu\/home\/amislove\/twittermood\/ (Accessed February 28 2014)"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-011-0120-x"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-012-0510-9"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-03260-3_37"},{"key":"e_1_2_1_5_1","unstructured":"Ryong Lee Shoko Wakamiya and Kazutoshi Sumiya: Exploring Geospatial Cognition based on Location-based Social Network Sites World Wide Web Journal (to ap ear)  Ryong Lee Shoko Wakamiya and Kazutoshi Sumiya: Exploring Geospatial Cognition based on Location-based Social Network Sites World Wide Web Journal (to ap ear)"}],"container-title":["ACM SIGWEB Newsletter"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2591453.2591457","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2591453.2591457","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T07:01:30Z","timestamp":1750230090000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2591453.2591457"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,4]]},"references-count":5,"journal-issue":{"issue":"Spring","published-print":{"date-parts":[[2014,4]]}},"alternative-id":["10.1145\/2591453.2591457"],"URL":"https:\/\/doi.org\/10.1145\/2591453.2591457","relation":{},"ISSN":["1931-1745","1931-1435"],"issn-type":[{"type":"print","value":"1931-1745"},{"type":"electronic","value":"1931-1435"}],"subject":[],"published":{"date-parts":[[2014,4]]},"assertion":[{"value":"2014-04-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}