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Modelling 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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 1 (January 2020) . - pp 150 - 176 Titre : Modelling perceived risks to personal privacy from location disclosure on online social networks Type de document : Article/Communication Auteurs : Fatma S. Alrayes, Auteur ; A.I. Abdelmoty, Auteur ; B.A. El-Geresy, Auteur ; G. Theodorakopoulos, Auteur Année de publication : 2020 Article en page(s) : pp 150 - 176 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] accès aux données localisées [Termes descripteurs IGN] appariement sémantique [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] échantillonnage (statistique) [Termes descripteurs IGN] géolocalisation [Termes descripteurs IGN] partage de données localisées [Termes descripteurs IGN] protection de la vie privée [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] vulnérabilité Résumé : (auteur) As users increasingly rely on online social networks for their communication activities, personal location data processing through such networks poses significant risks to users’ privacy. Location tracks can be mined with other shared information to extract rich personal profiles. To protect users’ privacy, online social networks face the challenge of ensuring transparent communication to users of how their data are processed, and explicitly obtaining users’ informed consent for the use of this data. In this paper, we explore the complex nature of the location disclosure problem and its risks to personal privacy. We evaluate, with an experiment involving 715 participants, the contributing factors to the perception of such risks with scenarios that mimic (a) realistic modes of interaction, where users are not fully aware of the extent of their location-related data being processed, and (b) with devised scenarios that deliberately inform users of the data they are sharing and its visibility to others. The results are used to represent the users’ perception of privacy risks when sharing their location information online and to derive a possible model of privacy risks associated with this sharing behaviour. Such a model can inform the design of privacy-aware online social networks to improve users’ trust and to ensure compliance with legal frameworks for personal privacy. Numéro de notice : A2020-009 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1654109 date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1654109 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94390 [article]

Volunteered geographic information systems: Technological design patterns / Jose Pablo Gómez‐Barrón in Transactions in GIS, Vol 23 n° 5 (October 2019)  

Public [article]  inTransactions in GIS > Vol 23 n° 5 (October 2019) . - pp 976 - 1007 Titre : Volunteered geographic information systems: Technological design patterns Type de document : Article/Communication Auteurs : Jose Pablo Gómez‐Barrón, Auteur ; Miguel Angel Manso-Callejo, Auteur ; Ramón Alcarria, Auteur Année de publication : 2019 Article en page(s) : pp 976 - 1007 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] acquisition de données [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] communauté virtuelle [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] GeoWeb [Termes descripteurs IGN] Infrastructure de données [Termes descripteurs IGN] interface mobile [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] système d'information géographique [Termes descripteurs IGN] traitement de données localisées Résumé : (auteur) Volunteered geographic information (VGI) has been studied extensively within various contexts, however, generally focusing on isolated aspects of data. Therefore, we still need to advance the structured knowledge of the mechanisms that affect and support its creation. This article aims to contribute to the integrated study of VGI systems (VGIS) in order to enhance design processes that lead to a more systematic and efficient VGI management. We define VGIS, their main components, and general architectures. Then, we use the service blueprinting technique to conduct the case study of several systems, identifying system actions to find the processes and technologies forming the different functional components of VGIS: elements of the technological infrastructure that implement diverse processes to facilitate participation and data management. Integrated in the data collection component, we also propose a typology of crowdsourcing tasks that—coupled with the functional components—establishes a foundation for VGIS research and design. We characterize these components, arguing that they are necessary in the development of VGIS, however, there is still a need for a more detailed study of the flow of processes and subprocesses and how they work under the criteria of different types of projects to continue facilitating their design. Numéro de notice : A2019-550 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12544 date de publication en ligne : 13/06/2019 En ligne : https://doi.org/10.1111/tgis.12544 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94200 [article]

Space, 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)  

Public [article]  inCartography and Geographic Information Science > Vol 46 n° 4 (July 2019) . - pp 334 - 346 Titre : Space, time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data Type de document : Article/Communication Auteurs : Zheye Wang, Auteur ; Xinyue Ye, Auteur Année de publication : 2019 Article en page(s) : pp 334 - 346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] espace-temps [Termes descripteurs IGN] gestion de crise [Termes descripteurs IGN] modèle de Markov [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] New York (Etats-Unis ; ville) [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] tempête Résumé : (Auteur) Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters. Numéro de notice : A2019-201 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1483740 date de publication en ligne : 18/06/2018 En ligne : https://doi.org/10.1080/15230406.2018.1483740 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92657 [article]

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Exploring 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)  

Public [article]  inInternational journal of geographical information science IJGIS > Vol 33 n° 5-6 (May - June 2019) . - pp 1196 - 1223 Titre : Exploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN Type de document : Article/Communication Auteurs : Xinyi Liu, Auteur ; Qunying Huang, Auteur ; Song Gao, Auteur Année de publication : 2019 Article en page(s) : pp 1196 - 1223 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] Twitter Mots-clés libres : density-based spatial clustering of applications with noise (DBSCAN) Résumé : (Auteur) The density-based spatial clustering of applications with noise (DBSCAN) method is often used to identify individual activity clusters (i.e., zones) using digital footprints captured from social networks. However, DBSCAN is sensitive to the two parameters, eps and minpts. This paper introduces an improved density-based clustering algorithm, Multi-Scaled DBSCAN (M-DBSCAN), to mitigate the detection uncertainty of clusters produced by DBSCAN at different scales of density and cluster size. M-DBSCAN iteratively calibrates suitable local eps and minpts values instead of using one global parameter setting as DBSCAN for detecting clusters of varying densities, and proves to be effective for detecting potential activity zones. Besides, M-DBSCAN can significantly reduce the noise ratio by identifying all points capturing the activities performed in each zone. Using the historic geo-tagged tweets of users in Washington, D.C. and in Madison, Wisconsin, the results reveal that: 1) M-DBSCAN can capture dispersed clusters with low density of points, and therefore detecting more activity zones for each user; 2) A value of 40 m or higher should be used for eps to reduce the possibility of collapsing distinctive activity zones; and 3) A value between 200 and 300 m is recommended for eps while using DBSCAN for detecting activity zones. Numéro de notice : A2019-445 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1563301 date de publication en ligne : 09/01/2019 En ligne : https://doi.org/10.1080/13658816.2018.1563301 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92781 [article]

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Understanding 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)  

Public [article]  inCartography and Geographic Information Science > vol 46 n° 3 (May 2019) . - pp 228 - 242 Titre : Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level Type de document : Article/Communication Auteurs : Jiang Juqin, Auteur ; Li Zhenlong, Auteur ; Xinyue Ye, Auteur Année de publication : 2019 Article en page(s) : pp 228 - 242 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] agrégation spatiale [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] données démographiques [Termes descripteurs IGN] données massives [Termes descripteurs IGN] données socio-économiques [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] géoétiquetage [Termes descripteurs IGN] régression géographiquement pondérée [Termes descripteurs IGN] Twitter Résumé : (Auteur) Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is widely recognized. Understanding the demographic and socioeconomic biases of Twitter users is critical for making reliable inferences on the attitudes and behaviors of the population. However, the existing global models cannot capture the regional variations of the demographic and socioeconomic biases. To bridge the gap, we modeled the relationships between different demographic/socioeconomic factors and geotagged Twitter users for the whole contiguous United States, aiming to understand how the demographic and socioeconomic factors relate to the number of Twitter users at county level. To effectively identify the local Twitter users for each county of the United States, we integrate three commonly used methods and develop a query approach in a high-performance computing environment. The results demonstrate that we can not only identify how the demographic and socioeconomic factors relate to the number of Twitter users, but can also measure and map how the influence of these factors vary across counties. Numéro de notice : A2019-093 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1434834 date de publication en ligne : 09/02/2018 En ligne : https://doi.org/10.1080/15230406.2018.1434834 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92338 [article]

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A 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)  

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Modeling 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)  

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CarSenToGram: 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)  

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Spatialities, 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])  

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SensePlace3: 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)  

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A spatial analysis of non‐English Twitter activity in Houston, TX / Matthew Haffner in Transactions in GIS, vol 22 n° 4 (August 2018)  

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Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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Combined geo-social search : computing top-k join queries over incomplete information / Yaron Kanza in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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A framework for annotating OpenStreetMap objects using geo-tagged tweets / Xin Chen in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

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TAGGS : 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)  

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