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Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media / Alexander Savelyev in International journal of cartography, Vol 6 n° 2 (July 2020)
[article]
Titre : Advancing the theory and practice of system evaluation: a case study in geovisual analytics of social media Type de document : Article/Communication Auteurs : Alexander Savelyev, Auteur ; Alan M. MacEachren, Auteur Année de publication : 2020 Article en page(s) : pp 202 - 221 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] approche participative
[Termes IGN] jeu de données localisées
[Termes IGN] logiciel de visualisation
[Termes IGN] réseau social
[Termes IGN] utilisateur
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) This paper advances the state-of-the-art in methodology design for empirical evaluation of (geo)visual analytics software. Specifically, we describe the process of design, development and application of a prototypical user study tailored to the evaluation of complex geovisual analytics tools that focus on social media analysis. We fist perform a synthesis of existing theory and best practices for software evaluation of comparable systems. We then demonstrate how the product of said synthesis – a methodological ‘check list’ – can be used to inform a proof-of-concept user study of an actual geovisual analytics software system. The resulting user study design accommodates for the use of real geographic social media datasets, the complexity of the intended analytical process, and for the learning challenges faced by the participants working with a fully-functional and mature geovisual analytics application, and is likely representative of a wide range of evaluation scenarios in (geo)visual analytics. A complete summary of all the study instruments is included to encourage their scrutiny, reuse and modification by others. Finally, we have discovered that participants’ curiosity and desire for autonomy played a noticeable role in the evaluation process – something not previously reported. Numéro de notice : A2020-373 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1637488 Date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.1080/23729333.2019.1637488 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95305
in International journal of cartography > Vol 6 n° 2 (July 2020) . - pp 202 - 221[article]Behavior-based location recommendation on location-based social networks / Seyyed Mohammadreza Rahimi in Geoinformatica, vol 24 n° 3 (July 2020)
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Titre : Behavior-based location recommendation on location-based social networks Type de document : Article/Communication Auteurs : Seyyed Mohammadreza Rahimi, Auteur ; Behrouz Far, Auteur ; Xin Wang, Auteur Année de publication : 2020 Article en page(s) : pp 477 – 504 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] interface web
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] réseau social géodépendant
[Termes IGN] système de recommandationRésumé : (auteur) Location recommendation methods on location-based social networks (LBSN) discover the locational preference of users along with their spatial movement patterns from users’ check-ins and provide users with recommendations of unvisited places. The growing popularity of LBSNs and abundance of shared location information has made location recommendation an active research area in the recent years. However, the existing methods suffer from one or more deficiencies such as data sparsity, cold-start users, ignoring users’ specific spatial and temporal behaviors, not utilizing the shared behaviors of the users. In this paper, we propose a novel location recommendation method, namely Behavior-based Location Recommendation (BLR). BLR recommends a location to a user based on the users’ repetitive behaviors and behaviors of similar users. Additionally, to better integrate the spatial information, BLR has two spatial components, a user-based spatial component to find the spatial preferences of the user, and a behavior-based spatial component to find locations of interest for different behaviors. Experimental studies on three real-world datasets show that BLR produces better location recommendations and can effectively address data sparsity and cold-start problems. Numéro de notice : A2020-370 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-019-00360-3 Date de publication en ligne : 25/05/2019 En ligne : https://doi.org/10.1007/s10707-019-00360-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95265
in Geoinformatica > vol 24 n° 3 (July 2020) . - pp 477 – 504[article]Learning evolving user’s behaviors on location-based social networks / Ruizhi Wu in Geoinformatica, vol 24 n° 3 (July 2020)
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Titre : Learning evolving user’s behaviors on location-based social networks Type de document : Article/Communication Auteurs : Ruizhi Wu, Auteur ; Guangchun Luo, Auteur ; Qi jin, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 713 – 743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] comportement
[Termes IGN] données localisées des bénévoles
[Termes IGN] filtrage d'information
[Termes IGN] géopositionnement
[Termes IGN] interaction homme-milieu
[Termes IGN] modèle dynamique
[Termes IGN] réseau social géodépendant
[Termes IGN] utilisateurRésumé : (auteur) With the popularity of smart phones, users’ activities on location-based social networks (LBSNs) evolve faster than traditional social networks. Existing models focus on modeling users’ long-term preferences, leveraging social collaborative filtering to enhance prediction performance. However, the dynamic mobility mechanism of user’s check-in behaviors on LBSNs is seldom considered. In this paper, we propose a new dynamic model that considers both geo-aware user preferences and the social interaction excitation arising from social connections to learn the dynamic mobility mechanism of user’s behaviors on LBSNs. Geo-aware location features, such as semantic features, latent features and dynamic features, are utilized to characterize the location information and reveal the evolution of the geographical impact of location. These geo-aware location features enable us to exploit user’s personal preferences. Meanwhile, we integrate a user’s social connections and friends’ preferences for modeling social interaction excitations. Finally, we jointly incorporate geo-aware user preference learning and social interaction excitation modeling to create a conditional intensity function for temporal point processes with which to explore the dynamic mobility mechanism of evolving user’s check-in behaviors on LBSNs. Extensive experiments on several real-world check-in datasets confirm that our proposed algorithm performs better than existing state-of-the-art methods. Numéro de notice : A2020-372 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00400-3 Date de publication en ligne : 16/03/2020 En ligne : https://doi.org/10.1007/s10707-020-00400-3 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95267
in Geoinformatica > vol 24 n° 3 (July 2020) . - pp 713 – 743[article]Micro diagrams: visualization of categorical point data from location-based social media / Mathias Gröbe in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)
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Titre : Micro diagrams: visualization of categorical point data from location-based social media Type de document : Article/Communication Auteurs : Mathias Gröbe, Auteur ; Dirk Burghardt, Auteur Année de publication : 2020 Article en page(s) : pp 305-320 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse spatiale
[Termes IGN] diagramme
[Termes IGN] données localisées des bénévoles
[Termes IGN] réseau social
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) Location-based social media data from different platforms such as Twitter and Flickr increasingly serve with their point-geocoded content as data sources for a variety of applications. The standard visualization method uses a derivation of point maps, which works well with a limited amount of data, but it suffers from weaknesses related to cluttering and overlapping, especially for sets of categories. We developed a new visualization method for categorical point data, called “Micro Diagrams”, which uses small diagrams to show the percentages of categories and the spatial distribution. The processing steps to derive the micro diagrams start with aggregating the points in a regular grid structure, which is followed by the selection of the diagram type that represents the numerical proportions and the application of a size scaling function to show the amounts of data. Various parameterization options are discussed and the influence of the color selection is analyzed. Finally, a case study combined with a user test presents the strengths and limits of the micro diagram method. Numéro de notice : A2020-189 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1733438 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.1080/15230406.2020.1733438 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95154
in Cartography and Geographic Information Science > Vol 47 n° 4 (July 2020) . - pp 305-320[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2020041 RAB Revue Centre de documentation En réserve L003 Disponible Objets connectés et mobilité urbaine : visualiser les déplacements des usagers de Twitter avec des graphes dynamiques / Françoise Lucchini in Mappemonde, n° 128 (juillet 2020)
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Titre : Objets connectés et mobilité urbaine : visualiser les déplacements des usagers de Twitter avec des graphes dynamiques Type de document : Article/Communication Auteurs : Françoise Lucchini, Auteur ; Olivier Gillet, Auteur ; Bernard Elissalde, Auteur ; Lény Grassot, Auteur ; Julien Baudry, Auteur ; Armelle Couillet, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] données issues des réseaux sociaux
[Termes IGN] internet des objets
[Termes IGN] mobilité urbaine
[Termes IGN] Paris (75)
[Termes IGN] point d'intérêt
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Avec le tournant numérique, les données issues des objets connectés constituent une ressource nouvelle pour la compréhension des rythmes urbains et des mobilités dans la ville. À l’aide des messages géolocalisés (1 540 000 tweets) des usagers du réseau social Twitter enregistrés durant l’année 2015, cet article présente un outil de visualisation des mobilités parisiennes en s’appuyant sur des graphes dynamiques. Nous montrons comment un algorithme de clustering nous permet de passer d’un message géolocalisé à un déplacement individuel puis à des trajectoires collectives. Ces dernières illustrent les mobilités préférentielles des usagers du réseau social dans Paris, ainsi que des zones de concentration et pôles d’intérêt. Numéro de notice : A2020-822 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/mappemonde.4297 En ligne : https://doi.org/10.4000/mappemonde.4297 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97250
in Mappemonde > n° 128 (juillet 2020)[article]Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data / Shivangi Srivastava in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkNeuroTPR: A neuro‐net toponym recognition model for extracting locations from social media messages / Jimin Wang in Transactions in GIS, Vol 24 n° 3 (June 2020)PermalinkDelineating and modeling activity space using geotagged social media data / Lingqian Hu in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)PermalinkA global analysis of cities’ geosocial temporal signatures for points of interest hours of operation / Kevin Sparks in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)PermalinkOnline flu epidemiological deep modeling on disease contact network / Liang Zhao in Geoinformatica, vol 24 n° 2 (April 2020)PermalinkSpatio-temporal mobility and Twitter: 3D visualisation of mobility flows / Joaquín Osorio Arjona in Journal of maps, vol 16 n° 1 ([02/01/2020])PermalinkPermalinkModelling perceived risks to personal privacy from location disclosure on online social networks / Fatma S. Alrayes in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)PermalinkPermalinkPermalinkVolunteered geographic information systems: Technological design patterns / Jose Pablo Gómez‐Barrón in Transactions in GIS, Vol 23 n° 5 (October 2019)PermalinkSpace, time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data / Zheye Wang in Cartography and Geographic Information Science, Vol 46 n° 4 (July 2019)PermalinkExploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN / Xinyi Liu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)PermalinkUnderstanding demographic and socioeconomic biases of geotagged Twitter users at the county level / Jiang Juqin in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)PermalinkA conceptual framework for studying collective reactions to events in location-based social media / Alexander Dunkel in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkModeling and visualizing semantic and spatio-temporal evolution of topics in interpersonal communication on Twitter / Caglar Koylu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)PermalinkCarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter / Caglar Koylu in Cartography and Geographic Information Science, Vol 46 n° 1 (January 2019)PermalinkNumérique et territoires / Philippe Cohard (2019)PermalinkA vélo au travers des Andes, pour OpenStreetMap / Anonyme in Géomatique expert, n° 126 (janvier - février 2019)PermalinkSpatialities, social Media and sentiment analysis: Exploring the potential of the detection tool SentiStrength / Christina Reithmeier in GI Forum, vol 2018 n° 2 ([01/09/2018])PermalinkSensePlace3: a geovisual framework to analyze place–time–attribute information in social media / Scott Pezanowski in Cartography and Geographic Information Science, Vol 45 n° 5 (August 2018)PermalinkA spatial analysis of non‐English Twitter activity in Houston, TX / Matthew Haffner in Transactions in GIS, vol 22 n° 4 (August 2018)PermalinkAssessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica, vol 22 n° 3 (July 2018)PermalinkCombined geo-social search : computing top-k join queries over incomplete information / Yaron Kanza in Geoinformatica, vol 22 n° 3 (July 2018)PermalinkA framework for annotating OpenStreetMap objects using geo-tagged tweets / Xin Chen in Geoinformatica, vol 22 n° 3 (July 2018)PermalinkTAGGS : grouping tweets to improve global geoparsing for disaster response / Jens A. de Bruijn in Journal of Geovisualization and Spatial Analysis, vol 2 n° 1 (June 2018)PermalinkThe limits of GIS: Towards a GIS of place / Alberto Giordano in Transactions in GIS, vol 22 n° 3 (June 2018)PermalinkHackAIR : towards raising awareness about air quality in Europe by developing a collective online platform / Evangelos Kosmidis in ISPRS International journal of geo-information, vol 7 n° 5 (May 2018)PermalinkThe national geographic characteristics of online public opinion propagation in China based on WeChat network / Chuan Ai in Geoinformatica, vol 22 n° 2 (April 2018)PermalinkA novel approach to site selection: collaborative multi-criteria decision making through geo-social network (case study: public parking) / Zeinab Neisani Samani in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkAnalyse du comportement des contributeurs dans l’Information Géographique Volontaire via la construction de réseaux sociaux / Quy Thy Truong (2018)PermalinkRaffinement de la localisation d’images provenant de sites participatifs pour la mise à jour de SIG urbain / Bernard Semaan (2018)PermalinkPermalinkWhat is so “hot” in heatmap? qualitative code cluster analysis with foursquare venue / Ilyoung Hong in Cartographica, vol 52 n° 4 (Winter 2017)PermalinkDepicting urban boundaries from a mobility network of spatial interactions : a case study of Great Britain with geo-located Twitter data / Junjun Yin in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkExtracting urban functional regions from points of interest and human activities on location-based social networks / Song Gao in Transactions in GIS, vol 21 n° 3 (June 2017)PermalinkInformation extraction and visualization from twitter considering spatial structure / Hideyuki Fujita in Cartographica, vol 52 n° 2 (Summer 2017)PermalinkDemand and supply of cultural ecosystem services: Use of geotagged photos to map the aesthetic value of landscapes in Hokkaido / Nobuhiko Yoshimura in Ecosystem Services, vol 24 (April 2017)PermalinkImproving large area population mapping using geotweet densities / Nirav N. Patel in Transactions in GIS, vol 21 n° 2 (April 2017)PermalinkBuilding social networks in volunteered geographic information communities: What contributor behaviours reveal about crowdsourced data quality / Quy Thy Truong (2017)PermalinkA modelling framework for the study of Spatial Data Infrastructures applied to coastal management and planning / Jade Georis-Creuseveau in International journal of geographical information science IJGIS, vol 31 n° 1-2 (January - February 2017)PermalinkPermalinkTowards a unified narrative-centric spatial clustering model of social media volunteered geographic information / Nick Bennett (2017)PermalinkSig participatif : gagnez du temps et de l'argent / Hubert d' Erceville in SIGmag, n° 11 (décembre 2016)PermalinkCrowdsourcing functions of the living city from Twitter and Foursquare data / Xiaolu Zhou in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)Permalink