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Auteur Jiue-An Yang |
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Similarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) / Chanwoo Jin in Transactions in GIS, Vol 24 n° 1 (February 2020)
[article]
Titre : Similarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) Type de document : Article/Communication Auteurs : Chanwoo Jin, Auteur ; Atsushi Nara, Auteur ; Jiue-An Yang, Auteur ; Ming-Hsiang Tsou, Auteur Année de publication : 2020 Article en page(s) : pp 104 - 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Bootstrap (statistique)
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] interpolation par pondération de zones
[Termes IGN] mesure de similitude
[Termes IGN] mobilité humaine
[Termes IGN] mobilité urbaine
[Termes IGN] origine - destinationRésumé : (auteur) Understanding diverse characteristics of human mobility provides profound knowledge of urban dynamics and complexity. Human movements are recorded in a variety of data sources and each describes unique mobility characteristics. Revealing similarity and difference in mobility data sources facilitates grasping comprehensive human mobility patterns. This study introduces a new method to measure similarities on two origin–destination (OD) matrices by spatially extending an image‐assessment tool, the structural similarity index (SSIM). The new measurement, spatially weighted SSIM (SpSSIM), utilizes weight matrices to overcome the SSIM sensitivity issue due to the ordering of OD pairs by explicitly defining spatial adjacency. To evaluate SpSSIM, we compared performances between SSIM and SpSSIM with resampling the orders of OD pairs and conducted bootstrapping to test the statistical significance of SpSSIM. As a case study, we compared OD matrices generated from three data sources in San Diego County, CA: U.S. Census‐based Longitudinal Employer–Household Dynamics Origin–Destination employment statistics, Twitter, and Instagram. The case study demonstrated that SpSSIM was able to capture similarities of mobility patterns between datasets that varied by distance. Some regions showed local dissimilarity while the global index indicated they were similar. The results enhance the understanding of complex mobility patterns from various datasets, including social media. Numéro de notice : A2020-104 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12590 Date de publication en ligne : 23/10/2019 En ligne : https://doi.org/10.1111/tgis.12590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94698
in Transactions in GIS > Vol 24 n° 1 (February 2020) . - pp 104 - 122[article]Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election / Ming-Hsiang Tsou in Cartography and Geographic Information Science, vol 40 n° 4 (September 2013)
[article]
Titre : Mapping social activities and concepts with social media (Twitter) and web search engines (Yahoo and Bing): a case study in 2012 US Presidential Election Type de document : Article/Communication Auteurs : Ming-Hsiang Tsou, Auteur ; Jiue-An Yang, Auteur ; Brian Spitzberg, Auteur ; Jean Marc Gawron, Auteur ; Dipak Gupta, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 337 - 348 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] comportement
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] élection
[Termes IGN] estimation par noyau
[Termes IGN] Etats-Unis
[Termes IGN] logiciel de navigation
[Termes IGN] moteur de recherche
[Termes IGN] ontologie
[Termes IGN] TwitterRésumé : (Auteur) We introduce a new research framework for analyzing the spatial distribution of web pages and social media (Twitter) messages with related contents, called Visualizing Information Space in Ontological Networks (VISION). This innovative method can facilitate the tracking of ideas and social events disseminated in cyberspace from a spatial-temporal perspective. Thousands of web pages and millions of tweets associated with the same keywords were converted into visualization maps using commercial web search engines (Yahoo application programming interface (API) and Bing API), a social media search engine (Twitter APIs), Internet Protocol (IP) geolocation methods, and Geographic Information Systems (GIS) functions (e.g., kernel density and raster-based map algebra methods). We found that comparing multiple web information landscapes with different keywords or different dates can reveal important spatial patterns and “geospatial fingerprints” for selected keywords. We used the 2012 US Presidential Election candidates as our case study to validate this method. We noticed that the weekly changes of the geographic probability of hosting “Barack Obama” or “Mitt Romney” web pages are highly related to certain major campaign events. Both attention levels and the content of the tweets were deeply impacted by Hurricane Sandy. This new approach may provide a new research direction for studying human thought, human behaviors, and social activities quantitatively. Numéro de notice : A2013-762 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2013.799738 En ligne : https://doi.org/10.1080/15230406.2013.799738 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32898
in Cartography and Geographic Information Science > vol 40 n° 4 (September 2013) . - pp 337 - 348[article]Réservation
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