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Auteur Oliver Lock |
Documents disponibles écrits par cet auteur (2)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesSocial media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? / Oliver Lock in Geo-spatial Information Science, vol 23 n° 4 (December 2020)
Titre : Social media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? Type de document : Article/Communication Auteurs : Oliver Lock, Auteur ; Christopher Pettit, Auteur Année de publication : 2020 Article en page(s) : pp 275 - 292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] artefact
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] données localisées des bénévoles
[Termes IGN] données massives
[Termes IGN] planification urbaine
[Termes IGN] réseau social
[Termes IGN] sentiment
[Termes IGN] Sydney (Nouvelle-Galles du Sud)
[Termes IGN] traitement du langage naturel
[Termes IGN] transport public
[Termes IGN] ville intelligenteRésumé : (auteur) We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion. Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city. With such pressures on existing public transportation systems, this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services. This research forms a case study of the use of passively collected forms of big data in cities – focusing on Sydney, Australia. Firstly, it examines social media data (Tweets) related to public transport performance. Secondly, it joins this to longitudinal big data – delay information continuously broadcast by the network over a year, thus forming hundreds of millions of data artifacts. Topics, tones, and sentiment are modeled using machine learning and Natural Language Processing (NLP) techniques. These resulting data, and models, are compared to opinions derived from a citizen survey among users. The validity of such data and models versus the intentions of users, in the context of systems that monitor and improve transport performance, are discussed. As such, key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques. Numéro de notice : A2020-787 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1815596 Date de publication en ligne : 21/09/2020 En ligne : https://doi.org/10.1080/10095020.2020.1815596 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96545
in Geo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 275 - 292[article]
Titre : Extended reality in spatial sciences: A review of research challenges and future directions Type de document : Article/Communication Auteurs : Arzu Çöltekin, Auteur ; Ian M. Lochhead, Auteur ; Marguerite Madden, Auteur ; Sidonie Christophe Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : n° 439 Note générale : bibliographie
The work in this manuscript has been partially funded by (a) Masaryk University internal research grant MUNI/A/1356/2019, (b) Learning Technologies Grant from the University of Georgia Center for Teaching and Learning and (c) University of Applied Sciences and Arts Northwestern Switzerland internal research grant “TP3 VR Labs» (T440-0002-100).Langues : Anglais (eng) Descripteur : [Termes IGN] environnement géographique virtuel
[Termes IGN] réalité augmentée
[Termes IGN] réalité mixte
[Termes IGN] réalité virtuelle
[Termes IGN] recherche et développement
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) This manuscript identifies and documents unsolved problems and research challenges in the extended reality (XR) domain (i.e., virtual (VR), augmented (AR), and mixed reality (MR)). The manuscript is structured to include technology, design, and human factor perspectives. The text is visualization/display-focused, that is, other modalities such as audio, haptic, smell, and touch, while important for XR, are beyond the scope of this paper. We further narrow our focus to mainly geospatial research, with necessary deviations to other domains where these technologies are widely researched. The main objective of the study is to provide an overview of broader research challenges and directions in XR, especially in spatial sciences. Aside from the research challenges identified based on a comprehensive literature review, we provide case studies with original results from our own studies in each section as examples to demonstrate the relevance of the challenges in the current research. We believe that this paper will be of relevance to anyone who has scientific interest in extended reality, and/or uses these systems in their research. Numéro de notice : A2020-418 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9070439 Date de publication en ligne : 15/07/2020 En ligne : https://doi.org/10.3390/ijgi9070439 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95527
in ISPRS International journal of geo-information > vol 9 n° 7 (July 2020) . - n° 439[article]
