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NeuroTPR: 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)  

Public [article]  inTransactions in GIS > Vol 24 n° 3 (June 2020) . - pp 719 - 735 Titre : NeuroTPR: A neuro‐net toponym recognition model for extracting locations from social media messages Type de document : Article/Communication Auteurs : Jimin Wang, Auteur ; Yingjie Hu, Auteur ; Kenneth Joseph, Auteur Année de publication : 2020 Article en page(s) : pp 719 - 735 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] flux de travaux [Termes descripteurs IGN] géolocalisation [Termes descripteurs IGN] précision sémantique [Termes descripteurs IGN] reconnaissance de noms [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] toponyme Résumé : (auteur) Social media messages, such as tweets, are frequently used by people during natural disasters to share real‐time information and to report incidents. Within these messages, geographic locations are often described. Accurate recognition and geolocation of these locations are critical for reaching those in need. This article focuses on the first part of this process, namely recognizing locations from social media messages. While general named entity recognition tools are often used to recognize locations, their performance is limited due to the various language irregularities associated with social media text, such as informal sentence structures, inconsistent letter cases, name abbreviations, and misspellings. We present NeuroTPR, which is a Neuro‐net ToPonym Recognition model designed specifically with these linguistic irregularities in mind. Our approach extends a general bidirectional recurrent neural network model with a number of features designed to address the task of location recognition in social media messages. We also propose an automatic workflow for generating annotated data sets from Wikipedia articles for training toponym recognition models. We demonstrate NeuroTPR by applying it to three test data sets, including a Twitter data set from Hurricane Harvey, and comparing its performance with those of six baseline models. Numéro de notice : A2020-445 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12627 date de publication en ligne : 14/05/2020 En ligne : https://doi.org/10.1111/tgis.12627 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95508 [article]

A 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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 4 (April 2020) . - pp 759 - 776 Titre : A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation Type de document : Article/Communication Auteurs : Kevin Sparks, Auteur ; Gautam Thakur, Auteur ; Amol Pasarkar, Auteur ; Marie Urban, Auteur Année de publication : 2020 Article en page(s) : pp 759 - 776 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] climat urbain [Termes descripteurs IGN] contenu généré par les utilisateurs [Termes descripteurs IGN] coutume [Termes descripteurs IGN] démographie [Termes descripteurs IGN] données géophysiques [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] estimation quantitative [Termes descripteurs IGN] ethnologie [Termes descripteurs IGN] géographie sociale [Termes descripteurs IGN] gestion urbaine [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] trace numérique Résumé : (auteur) The temporal nature of humans interaction with Points of Interest (POIs) in cities can differ depending on place type and regional location. Times when many people are likely to visit restaurants (place type) in Italy, may differ from times when many people are likely to visit restaurants in Lebanon (i.e. regional differences). Geosocial data are a powerful resource to model these temporal differences in cities, as traditional methods used to study cross-cultural differences do not scale to a global level. As cities continue to grow in population and economic development, research identifying the social and geophysical (e.g., climate) factors that influence city function remains important and incomplete. In this work, we take a quantitative approach, applying dynamic time warping and hierarchical clustering on temporal signatures to model geosocial temporal patterns for Retail and Restaurant Facebook POIs hours of operation for more than 100 cities in 90 countries around the world. Results show cities’ temporal patterns cluster to reflect the cultural region they represent. Furthermore, temporal patterns are influenced by a mix of social and geophysical factors. Trends in the data suggest social factors influence unique drops in temporal signatures, and geophysical factors influence when daily temporal patterns start and finish. Numéro de notice : A2020-294 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1615069 date de publication en ligne : 04/06/2019 En ligne : https://doi.org/10.1080/13658816.2019.1615069 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95126 [article]

Similarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) / Chanwoo Jin in Transactions in GIS, Vol 24 n° 1 (February 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 1 (February 2020) . - pp 104 - 122 Titre : Similarity measurement on human mobility data with spatially weighted structural similarity index (SpSSIM) Type de document : Article/Communication Auteurs : Chanwoo Jin, Auteur ; Atsushi Nara, Auteur ; Jiue-An Yang, Auteur ; Ming-Hsiang Tsou, Auteur Année de publication : 2020 Article en page(s) : pp 104 - 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] Bootstrap (statistique) [Termes descripteurs IGN] Californie (Etats-Unis) [Termes descripteurs IGN] carte de mobilité [Termes descripteurs IGN] données issues des réseaux sociaux [Termes descripteurs IGN] interpolation par pondération de zones [Termes descripteurs IGN] mesure de similitude [Termes descripteurs IGN] mobilité [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] origine - destination Résumé : (auteur) Understanding diverse characteristics of human mobility provides profound knowledge of urban dynamics and complexity. Human movements are recorded in a variety of data sources and each describes unique mobility characteristics. Revealing similarity and difference in mobility data sources facilitates grasping comprehensive human mobility patterns. This study introduces a new method to measure similarities on two origin–destination (OD) matrices by spatially extending an image‐assessment tool, the structural similarity index (SSIM). The new measurement, spatially weighted SSIM (SpSSIM), utilizes weight matrices to overcome the SSIM sensitivity issue due to the ordering of OD pairs by explicitly defining spatial adjacency. To evaluate SpSSIM, we compared performances between SSIM and SpSSIM with resampling the orders of OD pairs and conducted bootstrapping to test the statistical significance of SpSSIM. As a case study, we compared OD matrices generated from three data sources in San Diego County, CA: U.S. Census‐based Longitudinal Employer–Household Dynamics Origin–Destination employment statistics, Twitter, and Instagram. The case study demonstrated that SpSSIM was able to capture similarities of mobility patterns between datasets that varied by distance. Some regions showed local dissimilarity while the global index indicated they were similar. The results enhance the understanding of complex mobility patterns from various datasets, including social media. Numéro de notice : A2020-104 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12590 date de publication en ligne : 23/10/2019 En ligne : https://doi.org/10.1111/tgis.12590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94698 [article]

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 Affiliation des auteurs : non IGN 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]

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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 Affiliation des auteurs : non IGN 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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An exploratory analysis of usability of Flickr tags for land use/land cover attribution / Yingwei Yan in Geo-spatial Information Science, vol 22 n° 1 (March 2019)  

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Geographic space as a living structure for predicting human activities using big data / Bin Jiang in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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GeoTxt: A scalable geoparsing system for unstructured text geolocation / Morteza Karimzadeh in Transactions in GIS, vol 23 n° 1 (February 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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Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)  

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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)  

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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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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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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)  

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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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