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What is so “hot” in heatmap? qualitative code cluster analysis with foursquare venue / Ilyoung Hong in Cartographica, vol 52 n° 4 (Winter 2017)  

Public [article]  inCartographica > vol 52 n° 4 (Winter 2017) . - pp 332 - 348 Titre : What is so “hot” in heatmap? qualitative code cluster analysis with foursquare venue Type de document : Article/Communication Auteurs : Ilyoung Hong, Auteur ; Jin-Kyu Jung, Auteur Année de publication : 2017 Article en page(s) : pp 332 - 348 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatiale [Termes IGN] carte de densité de clics [Termes IGN] distribution spatiale [Termes IGN] réseau social géodépendant [Termes IGN] Seattle (Washington) [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Foursquare is a popular Web service and a representative location-based social network (LBSN) service using position data. Heatmap is a widely used means of geovisualization for analyzing social data with locational values. Until now, heatmap analysis of LBSN has focused on identifying quantitative distribution and patterns, with little consideration of the qualitative analysis of data content. Based on a case study of Foursquare venues and user-created content in Seattle, WA, this study conducts analyses assessing both the quantitative spatial distribution and the qualitative characteristics of coffee shops in the Seattle metropolitan area. It specifically proposes a new analytical method referred to as “code cluster,” which is designed to employ quantitative and qualitative approaches simultaneously. The significance of this method is its capacity to explain geographical differences in terms of qualitative traits in cluster regions, in addition to analyzing their spatial characteristics and distributions. In introducing this new hybrid approach, our aims are to reflect the original intent and essence of the data throughout the research process and to make further efforts to analyze and interpret the contextualized meanings. This will be possible through integration of advanced spatial analysis, geovisualization, and qualitative research that build on current geographic and geovisual research with big data. Numéro de notice : A2017-830 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/cart.52.4.2016-0005 En ligne : https://doi.org/10.3138/cart.52.4.2016-0005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89364 [article]

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