Multi-scaled Spatial Analytics on Discovering Latent Social Events for Smart Urban Services
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, O-Joun | - |
dc.contributor.author | Kim, Yunhu | - |
dc.contributor.author | Hoang Long Nguyen | - |
dc.contributor.author | Jung, Jai E. | - |
dc.date.available | 2019-01-22T14:20:15Z | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 0948-695X | - |
dc.identifier.issn | 0948-6968 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/1500 | - |
dc.description.abstract | The goal of this paper is to discover latent social events from social media for sensitively understanding social opinions that appeared within a city. The latent social event indicates a regional and inconspicuous social event which is mostly buried under macroscopic trends or issues. To detect the latent social event, we propose three methods: i) discovering areas-of-interest (AOIs), ii) allocating social texts to the AOIs, and iii) detecting social events in each AOI. The AOIs can be composed by grouping social texts which are topically and spatially homogeneous. To make the AOIs dynamic and incremental, we use windows for allocating a social text to an adequate AOI. Lastly, the latent social events are detected from the AOI on the basis of keywords and temporal distribution of the social texts. Although, in this study, we limited the proposed method into analyzing social media, it could be extended to detecting events among agents/things/sensors. | - |
dc.format.extent | 16 | - |
dc.publisher | GRAZ UNIV TECHNOLGOY, INST INFORMATION SYSTEMS COMPUTER MEDIA-IICM | - |
dc.title | Multi-scaled Spatial Analytics on Discovering Latent Social Events for Smart Urban Services | - |
dc.type | Article | - |
dc.identifier.doi | 10.3217/jucs-024-03-0322 | - |
dc.identifier.bibliographicCitation | JOURNAL OF UNIVERSAL COMPUTER SCIENCE, v.24, no.3, pp 322 - 337 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000436236400006 | - |
dc.identifier.scopusid | 2-s2.0-85050398697 | - |
dc.citation.endPage | 337 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 322 | - |
dc.citation.title | JOURNAL OF UNIVERSAL COMPUTER SCIENCE | - |
dc.citation.volume | 24 | - |
dc.type.docType | Article | - |
dc.publisher.location | 오스트리아 | - |
dc.subject.keywordAuthor | Social event detection | - |
dc.subject.keywordAuthor | Area-of-interest | - |
dc.subject.keywordAuthor | Social opinion mining | - |
dc.subject.keywordAuthor | Spatio-temporal analysis | - |
dc.subject.keywordPlus | FRAMEWORK | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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