Descripteur
Documents disponibles dans cette catégorie (116)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
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)
[article]
Titre : SensePlace3: a geovisual framework to analyze place–time–attribute information in social media Type de document : Article/Communication Auteurs : Scott Pezanowski, Auteur ; Alan M. MacEachren, Auteur ; Alexander Savelyev, Auteur ; Anthony C. Robinson, Auteur Année de publication : 2018 Article en page(s) : pp 420 - 437 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] analyse spatio-temporelle
[Termes IGN] données massives
[Termes IGN] environnement de développement
[Termes IGN] gestion de crise
[Termes IGN] réseau social
[Termes IGN] trace numérique
[Termes IGN] Twitter
[Vedettes matières IGN] GéovisualisationRésumé : (Auteur) SensePlace3 (SP3) is a geovisual analytics framework and web application that supports overview + detail analysis of social media, focusing on extracting meaningful information from the Twitterverse. SP3 leverages social media related to crisis events. It differs from most existing systems by enabling an analyst to obtain place-relevant information from tweets that have implicit as well as explicit geography. Specifically, SP3 includes not just the ability to utilize the explicit geography of geolocated tweets but also analyze implicit geography by recognizing and geolocating references in both tweet text, which indicates locations tweeted about, and in Twitter profiles, which indicates locations affiliated with users. Key features of SP3 reported here include flexible search and filtering capabilities to support information foraging; an ingest, processing, and indexing pipeline that produces near real-time access for big streaming data; and a novel strategy for implementing a web-based multi-view visual interface with dynamic linking of entities across views. The SP3 system architecture was designed to support crisis management applications, but its design flexibility makes it easily adaptable to other domains. We also report on a user study that provided input to SP3 interface design and suggests next steps for effective spatiotemporal analytics using social media sources. Numéro de notice : A2018-272 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1370391 Date de publication en ligne : 11/09/2017 En ligne : https://doi.org/10.1080/15230406.2017.1370391 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90336
in Cartography and Geographic Information Science > Vol 45 n° 5 (August 2018) . - pp 420 - 437[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2018051 RAB Revue Centre de documentation En réserve L003 Disponible A spatial analysis of non‐English Twitter activity in Houston, TX / Matthew Haffner in Transactions in GIS, vol 22 n° 4 (August 2018)
[article]
Titre : A spatial analysis of non‐English Twitter activity in Houston, TX Type de document : Article/Communication Auteurs : Matthew Haffner, Auteur Année de publication : 2018 Article en page(s) : pp 913 - 929 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] Houston (Texas)
[Termes IGN] langage naturel (informatique)
[Termes IGN] régression
[Termes IGN] TwitterRésumé : (Auteur) The use of social media data in geographic studies has become common, yet the question of social media's validity in such contexts is often overlooked. Social media data suffers from a variety of biases and limitations; nevertheless, with a proper understanding of the drawbacks, these data can be powerful. As cities seek to become “smarter,” they can potentially use social media data to creatively address the needs of their most vulnerable groups, such as ethnic minorities. However, questions remain unanswered regarding who uses these social networking platforms, how people use these platforms, and how representative social media data is of users' everyday lives. Using several forms of regression, I explore the relationships between a conventional data source (the U.S. Census) and a subset of Twitter data potentially representative of minority groups: tweets created by users with an account language other than English. A considerable amount of non‐stationarity is uncovered, which should serve as a warning against sweeping statements regarding the demographics of users and where people prefer to post. Further, I find that precisely located Twitter data informs us more about the digital status of places and less about users' day‐to‐day travel patterns. Numéro de notice : A2018-574 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12335 Date de publication en ligne : 11/04/2018 En ligne : https://doi.org/10.1111/tgis.12335 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92320
in Transactions in GIS > vol 22 n° 4 (August 2018) . - pp 913 - 929[article]Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica, vol 22 n° 3 (July 2018)
[article]
Titre : Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets Type de document : Article/Communication Auteurs : Ming Li, Auteur ; Rene Westerholt, Auteur ; Hongchao Fan, Auteur ; Alexander Zipf, Auteur Année de publication : 2018 Article en page(s) : pp 541 - 561 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] comportement
[Termes IGN] jeu de données localisées
[Termes IGN] modèle de simulation
[Termes IGN] prévision
[Termes IGN] réseau social géodépendant
[Termes IGN] villeRésumé : (Auteur) Location-based social networks (LBSN) have provided new possibilities for researchers to gain knowledge about human spatiotemporal behavior, and to make predictions about how people might behave through space and time in the future. An important requirement of successfully utilizing LBSN in these regards is a thorough understanding of the respective datasets, including their inherent potential as well as their limitations. Specifically, when it comes to predictions, we must know what we can actually expect from the data, and how we could maximize their usefulness. Yet, this knowledge is still largely lacking from the literature. Hence, this work explores one particular aspect which is the theoretical predictability of LBSN datasets. The uncovered predictability is represented with an interval. The lower bound of the interval corresponds to the amount of regular behaviors that can easily be anticipated, and represents the correct predication rate that any algorithm should be able to achieve. The upper bound corresponds to the amount of information that is contained in the dataset, and represents the maximum correct prediction rate that cannot be exceeded by any algorithms. Three Foursquare datasets from three American cities are studied as an example. It is found that, within our investigated datasets, the lower bound of predictability of the human spatiotemporal behavior is 27%, and the upper bound is 92%. Hence, the inherent potentials of the dataset for predicting human spatiotemporal behavior are clarified, and the revealed interval allows a realistic assessment of the quality of predictions and thus of associated algorithms. Additionally, in order to provide further insight into the practical use of the dataset, the relationship between the predictability and the check-in frequencies are investigated from three different perspectives. It was found that the individual perspective provides no significant correlations between the predictability and the check-in frequency. In contrast, the same two quantities are found to be negatively correlated from temporal and spatial perspectives. Our study further indicates that the heavily frequented contexts and some extraordinary geographic features such as airports could be good starting points for effective improvements of prediction algorithms. In general, this research provides novel knowledge regarding the nature of the LBSN dataset and practical insights for a more reasonable utilization of the dataset. Numéro de notice : A2018-349 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-016-0279-5 Date de publication en ligne : 25/11/2016 En ligne : https://doi.org/10.1007/s10707-016-0279-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90758
in Geoinformatica > vol 22 n° 3 (July 2018) . - pp 541 - 561[article]Combined geo-social search : computing top-k join queries over incomplete information / Yaron Kanza in Geoinformatica, vol 22 n° 3 (July 2018)
[article]
Titre : Combined geo-social search : computing top-k join queries over incomplete information Type de document : Article/Communication Auteurs : Yaron Kanza, Auteur ; Mirit Shalem, Auteur Année de publication : 2018 Article en page(s) : pp 615 - 660 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] approximation
[Termes IGN] données localisées
[Termes IGN] jointure
[Termes IGN] requête spatiale
[Termes IGN] réseau socialRésumé : (Auteur) Geo-social data sets, which fuse the social and the geospatial facets of data, are vibrant data sources that associate people and activities with locations. In a combined geo-social search, several search queries are posed over geospatial and social data sources, or over data sources with both geospatial and social facets; and the search results, provided as ranked lists of items, are integrated by associating matching items, yielding combinations. Each combination has a score which is a function of the scores of the items it comprises, and the goal is to compute the k combinations with the highest score, that is, the top-k combinations. However, since geo-social data sources are heterogeneous, data items may not have matching items in all the ranked lists. Such items cannot be included in complete combinations. Hence, we study the approach where combinations are padded by nulls for missing items, as in outer-join. A combination is maximal if it cannot be extended by replacing a null by an item. We show that if some of the top-k maximal combinations contain null values, the computation requires reading entire lists, and hence, traditional top-k algorithms and optimization techniques are not as effective as in the case of an ordinary top-k join. Thus, we present two novel algorithms for computing the top-k maximal combinations. One novel algorithm is instance optimal over the class of algorithms that compute a ??approximation to the answer. The second algorithm is more efficient than the modification of two common top-k algorithms to compute maximal combinations. We show this analytically, and experimentally over real and synthetic data. Numéro de notice : A2018-370 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-017-0297-y Date de publication en ligne : 25/03/2017 En ligne : https://doi.org/10.1007/s10707-017-0297-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90762
in Geoinformatica > vol 22 n° 3 (July 2018) . - pp 615 - 660[article]A framework for annotating OpenStreetMap objects using geo-tagged tweets / Xin Chen in Geoinformatica, vol 22 n° 3 (July 2018)
[article]
Titre : A framework for annotating OpenStreetMap objects using geo-tagged tweets Type de document : Article/Communication Auteurs : Xin Chen, Auteur ; Hoang Vo, Auteur ; Yu Wang, Auteur ; Fusheng Wang, Auteur Année de publication : 2018 Article en page(s) : pp 589 - 613 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] corpus
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] enrichissement sémantique
[Termes IGN] géobalise
[Termes IGN] intégration de données
[Termes IGN] objet géographique
[Termes IGN] OpenStreetMap
[Termes IGN] TwitterRésumé : (Auteur) Recent years have witnessed an explosion of geospatial data, especially in the form of Volunteered Geographic Information (VGI). As a prominent example, OpenStreetMap (OSM) creates a free editable map of the world from a large number of contributors. On the other hand, social media platforms such as Twitter or Instagram supply dynamic social feeds at population level. As much of such data is geo-tagged, there is a high potential on integrating social media with OSM to enrich OSM with semantic annotations, which will complement existing objective description oriented annotations to provide a broader range of annotations. In this paper, we propose a comprehensive framework on integrating social media data and VGI data to derive knowledge about geographical objects, specifically, top relevant annotations from tweets for objects in OSM. We first integrate geo-tagged tweets with OSM data with scalable spatial queries running on MapReduce. We propose a frequency based method for annotating boundary based geographic objects (a polygon), and a probability based method for annotating point based geographic objects (Latitude and Longitude), with consideration of noise. We evaluate our methods using a large geo-tagged tweets corpus and representative geographic objects from OSM, which demonstrates promising results through ground-truth comparison and case studies. We are able to produce up to 80% correct names for geographical objects and discover implicitly relevant information, such as popular exhibitions of a museum, the nicknames or visitors’ impression to a tourism attraction. Numéro de notice : A2018-369 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-018-0323-8 Date de publication en ligne : 20/06/2018 En ligne : https://doi.org/10.1007/s10707-018-0323-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90760
in Geoinformatica > vol 22 n° 3 (July 2018) . - pp 589 - 613[article]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)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