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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)
[article]
Titre : CarSenToGram: geovisual text analytics for exploring spatiotemporal variation in public discourse on Twitter Type de document : Article/Communication Auteurs : Caglar Koylu, Auteur ; Ryan Larson, Auteur ; Bryce J. Dietrich, Auteur ; Kang-Pyo Lee, Auteur Année de publication : 2019 Article en page(s) : pp 57 - 71 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse du discours
[Termes IGN] analyse géovisuelle
[Termes IGN] cartogramme
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] corpus
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] exploration de données
[Termes IGN] sentiment
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Assessing the impact of events on the evolution of online public discourse is challenging due to the lack of data prior to the event and appropriate methodologies for capturing the progression of tenor of public discourse, both in terms of their tone and topic. In this article, we introduce a geovisual analytics framework, CarSenToGram, which integrates topic modeling and sentiment analysis with cartograms to identify the changing dynamics of public discourse on a particular topic across space and time. The main novelty of CarSenToGram is coupling comprehensible spatiotemporal overviews of the overall distribution, topical and sentiment patterns with increasing levels of information supported by zoom and filter, and details-on-demand interactions. To demonstrate the utility of CarSenToGram, in this article, we analyze tweets related to immigration the month before and after the 27 January 2017 travel ban in order to reveal insights into one of the defining moments of President Trump’s first year in office. Not only do we find that the travel ban influenced online public discourse and sentiment on immigration, but it also highlighted important partisan divisions within the US. Numéro de notice : A2019-012 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1510343 Date de publication en ligne : 18/09/2018 En ligne : https://doi.org/10.1080/15230406.2018.1510343 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91661
in Cartography and Geographic Information Science > Vol 46 n° 1 (January 2019) . - pp 57 - 71[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2019011 RAB Revue Centre de documentation En réserve L003 Disponible Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)
[article]
Titre : Urban impervious surface estimation from remote sensing and social data Type de document : Article/Communication Auteurs : Yan Yu, Auteur ; Jun Li, Auteur ; Changyu Zhu, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2018 Article en page(s) : pp 771 - 780 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] base de données routières
[Termes IGN] Canton (Kouangtoung)
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] données vectorielles
[Termes IGN] Google Maps
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] régression multiple
[Termes IGN] réseau routier
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (auteur) We propose an inspiring approach for accurate impervious surface estimation based on the integration of remote sensing and social data. The proposed approach exploits the strengths of two kind of heterogeneous features, i.e., physical features and social features, where the former ones are derived by a morphological attribute profiles-guided spectral mixture analysis model using remote sensing imagery, and the latter ones are obtained from the normalized kernel density of point of interest and vector road datasets. These two features are then integrated using a multivariable linear regression model to estimate impervious surfaces. The proposed method has been tested in the main urban area of Guangzhou, China, in pixel level and parcel level, respectively. The obtained results, with the overall RMSE of 10.98% and 10.90% for pixel level and parcel level, respectively, demonstrate the good performance of integrating remote sensing imagery and social data for mapping of urban impervious surface. Numéro de notice : A2018-549 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.12.771 Date de publication en ligne : 01/12/2018 En ligne : https://doi.org/10.14358/PERS.84.12.771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91622
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 12 (December 2018) . - pp 771 - 780[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2018121 RAB Revue Centre de documentation En réserve L003 Disponible A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks / Lin Wan in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)
[article]
Titre : A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks Type de document : Article/Communication Auteurs : Lin Wan, Auteur ; Yuming Hong, Auteur ; Zhou Huang, Auteur ; Xia Peng, Auteur ; Ran Li, Auteur Année de publication : 2018 Article en page(s) : pp 2225 - 2246 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] apprentissage automatique
[Termes IGN] calcul d'itinéraire
[Termes IGN] classification bayesienne
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] données météorologiques
[Termes IGN] exploration de données géographiques
[Termes IGN] géobalise
[Termes IGN] image Flickr
[Termes IGN] Pékin (Chine)
[Termes IGN] point d'intérêtRésumé : (Auteur) Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts personalized tourist routes for travelers by mining their geographical preferences from these location-tagged data. Our method trains two types of base classifiers to jointly predict the next travel destination: (1) The K-nearest neighbor (KNN) classifier quantifies users’ location history, weather condition, temperature and seasonality and uses a feature-weighted distance model to predict a user’s personalized interests in an unvisited location. (2) A Bayes classifier introduces a smooth kernel function to estimate a-priori probabilities of features and then combines these probabilities to predict a user’s latent interests in a location. All the outcomes from these subclassifiers are merged into one final prediction result by using the Borda count voting method. We evaluated our method on geo-tagged Flickr photos and Beijing weather data collected from 1 January 2005 to 1 July 2016. The results demonstrated that our ensemble approach outperformed 12 other baseline models. In addition, the results showed that our framework has better prediction accuracy than do context-aware significant travel-sequence-patterns recommendations and frequent travel-sequence patterns. Numéro de notice : A2018-523 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1458988 Date de publication en ligne : 03/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1458988 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91348
in International journal of geographical information science IJGIS > vol 32 n° 11-12 (November - December 2018) . - pp 2225 - 2246[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2018061 RAB Revue Centre de documentation En réserve L003 Disponible Analyzing the effect of earthquakes on OpenStreetMap contribution patterns and tweeting activities / Ahmed Ahmouda in Geo-spatial Information Science, vol 21 n° 3 (October 2018)
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Titre : Analyzing the effect of earthquakes on OpenStreetMap contribution patterns and tweeting activities Type de document : Article/Communication Auteurs : Ahmed Ahmouda, Auteur ; Hartwig H. Hochmair, Auteur ; Sreten Cvetojevic, Auteur Année de publication : 2018 Article en page(s) : pp 195 - 212 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] catastrophe naturelle
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] Italie
[Termes IGN] Népal
[Termes IGN] OpenStreetMap
[Termes IGN] séismeRésumé : (Auteur) Natural disasters, such as wildfires, earthquakes, landslides, or floods, lead to an increase in topical information shared on social media and in increased mapping activities in volunteered geographic information (VGI) platforms. Using earthquakes in Nepal and Central Italy as case studies, this research analyzes the effects of natural disasters on short-term (weeks) and longer-term (half year) changes in OpenStreetMap (OSM) mapping behavior and tweet activities in the affected regions. An increase of activities in OSM during the events can be partially attributed to those focused OSM mapping campaigns, for example, through the Humanitarian OSM Team (HOT). Using source tags in OSM change-sets, it was found that only a small portion of external mappers actually travels to the affected regions, whereas the majority of external mappers relies on desktop mapping instead. Furthermore, the study analyzes the spatio-temporal sequence of posted tweets together with keyword filters to identify a subset of users who most likely traveled to the affected regions for support and rescue operations. It also explores where, geographically, earthquake information spreads within social networks. Numéro de notice : A2018-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2018.1498666 Date de publication en ligne : 27/07/2018 En ligne : https://doi.org/10.1080/10095020.2018.1498666 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93310
in Geo-spatial Information Science > vol 21 n° 3 (October 2018) . - pp 195 - 212[article]NRand‐K : Minimizing the impact of location obfuscation in spatial analysis / Mayra Zurbaran in Transactions in GIS, vol 22 n° 5 (October 2018)
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Titre : NRand‐K : Minimizing the impact of location obfuscation in spatial analysis Type de document : Article/Communication Auteurs : Mayra Zurbaran, Auteur ; Pedro Wightman, Auteur ; Maria Antonia Brovelli, Auteur ; Daniele Oxoli, Auteur Année de publication : 2018 Article en page(s) : pp 1257 - 1274 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse comparative
[Termes IGN] anonymisation
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] exploration de données géographiques
[Termes IGN] protection de la vie privéeRésumé : (Auteur) Location privacy, or geoprivacy, is critical to secure users’ privacy in context‐aware applications. Location‐based services pose privacy risks for users, due to the inferences that could be made about them from their location information and the potential misuse of this data by service providers or third‐party companies. A common solution is to apply masking or location obfuscation, which degrades location information quality while keeping a geographic coordinate structure. However, there is a trade‐off between privacy, quality of service, and quality of information, the last one being a valuable asset for companies. NRand is a location privacy mechanism with obfuscation capabilities and resistance against filtering attacks. In order to minimize the impact on location information quality, NRand‐K has been introduced. This algorithm is designed for use when releasing location information to third parties or as open data with privacy concerns. To assess the impact of location obfuscation on exploratory spatial data analysis (ESDA), a comparison is performed between obfuscated data with NRand, NRand‐K, and unaltered data. For the experiments, geolocated tweets collected during the Central Italy 2016 earthquake are used. Results show that NRand‐K reduces the impact on ESDA, where inferences were similar to those obtained with the unaltered data. Numéro de notice : A2018-573 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12462 Date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1111/tgis.12462 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92298
in Transactions in GIS > vol 22 n° 5 (October 2018) . - pp 1257 - 1274[article]Spatial discontinuities, health and mobility - What do the Google's POIs and tweets tell us about Bangkok's (Thailand) structures and spatial dynamics? / Alexandre Cebeillac in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)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])PermalinkInterplay between urban communities and human‐crowd mobility: A study using contributed geospatial data sources / Mohammad Forghani in Transactions in GIS, vol 22 n° 4 (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)PermalinkCombining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment / Bernd Resch in Cartography and Geographic Information Science, Vol 45 n° 4 (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)PermalinkEPLA : efficient personal location anonymity / Dapeng Zhao in Geoinformatica, vol 22 n° 1 (January 2018)PermalinkExtraction of pluvial flood relevant volunteered geographic information (VGI) by deep learning from user generated texts and photos / Yu Feng in ISPRS International journal of geo-information, vol 7 n° 2 (February 2018)PermalinkRaffinement de la localisation d’images provenant de sites participatifs pour la mise à jour de SIG urbain / Bernard Semaan (2018)PermalinkA cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data / Qunying Huang in Computers, Environment and Urban Systems, vol 66 (November 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)PermalinkGlobal multi-layer network of human mobility / Alexander Belyi in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)PermalinkInformation extraction and visualization from twitter considering spatial structure / Hideyuki Fujita in Cartographica, vol 52 n° 2 (Summer 2017)PermalinkDesign and evaluation of a geovisual analytics system for uncovering patterns in spatio-temporal event data / Anthony C. Robinson in Cartography and Geographic Information Science, Vol 44 n° 3 (May 2017)PermalinkDeveloping an integrated cloud-based spatial-temporal system for monitoring phenology / M. Cope in Ecological Informatics, vol 39 (May 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)PermalinkExploiting location-aware social networks for efficient spatial query processing / Liang Tang in Geoinformatica, vol 21 n° 1 (January - March 2017)PermalinkTowards a unified narrative-centric spatial clustering model of social media volunteered geographic information / Nick Bennett (2017)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)PermalinkAutomatic targeted-domain spatiotemporal event detection in twitter / Ting Hua in Geoinformatica, vol 20 n° 4 (October - December 2016)PermalinkActivity patterns, socioeconomic status and urban spatial structure: what can social media data tell us? / Qunying Huang in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkDiscovery of local topics by using latent spatio-temporal relationships in geo-social media / Kyoung-Sook Kim in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkExploration of spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks / Enrico Steiger in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkFinding spatial outliers in collective mobility patterns coupled with social ties / Monica Wachowicz in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkIntegrating social network data into GISystems / Clio Andris in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)PermalinkGeo-temporal Twitter demographics / Paul A. Longley in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkJoining spatial distribution visualisation tools with social media data using free and open source software : extended abstract / Mayra Zurbaran (2016)PermalinkAn advanced systematic literature review on spatiotemporal analyses of twitter-data / Enrico Steiger in Transactions in GIS, vol 19 n° 6 (December 2015)PermalinkTriangulating social multimedia content for event localization using Flickr and Twitter / George Panteras in Transactions in GIS, vol 19 n° 5 (October 2015)PermalinkAnalyse du comportement d’annotation du réseau social d’un utilisateur pour la détection des intérêts. Application sur Delicious / Manel Mezghani in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 20 n° 4 (juillet - août 2015)PermalinkPermalinkA geographic approach for combining social media and authoritative data towards identifying useful information for disaster management / João Porto de Albuquerque in International journal of geographical information science IJGIS, vol 29 n° 4 (April 2015)PermalinkObject selection in map generalization using geosocial network data: A case study in Wuhan, China / Hao Luo in Geomatica, vol 69 n° 1 (March 2015)PermalinkGeo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan / Mohamed Bakillah in International journal of geographical information science IJGIS, vol 29 n° 2 (February 2015)PermalinkMapping 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)PermalinkAssessing the veracity of methods for extracting place semantics from Flickr tags / William A Mackaness in Transactions in GIS, vol 17 n° 4 (August 2013)PermalinkGeo-tagged Twitter collection and visualization system / Hideyuki Fujita in Cartography and Geographic Information Science, vol 40 n° 3 (June 2013)PermalinkDemarcating new boundaries: mapping virtual polycentric communities through social media content / Anthony Stefanidis in Cartography and Geographic Information Science, vol 40 n° 2 (March 2013)PermalinkEvaluating the “geographical awareness” of individuals: an exploratory analysis of Twitter data / Chen Xu in Cartography and Geographic Information Science, vol 40 n° 2 (March 2013)PermalinkAn ontology-based approach to incorporate user-generated geo-content into SDI / D.P. Deng (20/10/2011)Permalink