Registo fonte: Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?

Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?

Human mobilities in urban areas have an impact on the spread of infectious diseases, including those caused by mosquito-borne diseases like dengue and Zika virus. Therefore, finding appropriate data and methods to perform spatial analyses of mobilities is a critical issue. The emergence of substanti...

ver descrição completa

Na minha lista:

Detalhes bibliográficos
Publicado no:	URI:https://journals.openedition.org/netcom,
Auteurs principaux:	Cebeillac, Alexandre, Daudé, Eric, Huraux, Thomas
Formato:	Article ou chapitre numérique
Idioma:	Anglais
Publicado em:	Netcom 2018
Assuntos:	Twitter mobilité quotidienne Google POI Bangkok urban mobility
Acesso em linha:	Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM

id	openedition-oai:revues.org:netcom_2725
record_format	openedition
spelling	openedition-oai:revues.org:netcom_2725 https://doi.org/10.4000/netcom.2725 urn:doi:10.4000/netcom.2725 en https://journals.openedition.org/netcom/2725 2018-03-29T02:00:00Z info:eu-repo/semantics/openAccess article info:eu-repo/semantics/article urn:handle:20.500.13089/ij8a https://creativecommons.org/licenses/by-nc-nd/4.0/ Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ? Netcom Netcom Association info:eu-repo/semantics/reference/issn/2431-210X info:eu-repo/semantics/reference/issn/0987-6014 URI:https://journals.openedition.org/netcom Cebeillac, Alexandre Daudé, Eric Huraux, Thomas Twitter mobilité quotidienne Google POI Bangkok Twitter urban mobility Google POI Bangkok Human mobilities in urban areas have an impact on the spread of infectious diseases, including those caused by mosquito-borne diseases like dengue and Zika virus. Therefore, finding appropriate data and methods to perform spatial analyses of mobilities is a critical issue. The emergence of substantial amount of geolocated data, which is easily available on the Internet, has a great potential in mobility researches, especially when paired with land use, following the activity-space concept. This paper, focused on the dengue endemic mega-city of Bangkok (Thailand), explores the potentialities of (A) using a land use classification from Google’s points of interest (POIs) to assess the likelihood of performing an activity from (B) a large dataset of individual geolocated tweets to characterize and quantify daily mobility. These emerging data sources allow the characterization of (C) the rhythms of daily mobility in Bangkok, from the perspective of (1) the macroscopic urban pulse and (2) the rhythms and aims for individual movement. The advantages and limitations of this kind of data will be finally discussed regarding dengue epidemics. Les mobilités notamment quotidiennes sont un facteur qui contribue à la propagation de maladies infectieuses en milieu urbain. C’est le cas pour les arboviroses transmises par des moustiques du genre Aedes comme la dengue ou le Zika. L’utilisation de données sociales de plus en plus précises et de méthodes d’analyses spatiales contribue à enrichir notre compréhension de ces mécanismes sous-jacents. L’émergence d’une grande quantité de données géolocalisées aisément accessible sur Internet offre de nombreuses pistes de recherches sur les mobilités, notamment si ces dernières sont couplées à des données d’utilisation du sol, ce qui permet de construire des espaces d’activités. Cet article prend pour fil conducteur la dengue, endémique à Bangkok (Thaïlande), pour explorer les potentiels (A) d’une classification de l’utilisation du sol construite à partir des points d’intérêts (POI, Google Map) afin d’estimer la probabilité pour un individu d’effectuer une activité en mobilisant (B) une grande base de données de Tweets géolocalisés qui permet de quantifier les mobilités quotidiennes individuelles. Ces informations ainsi construites permettent (C) une caractérisation des mobilités quotidiennes à Bangkok, d’un point de macroscopique (pulsation urbaine) et des rythmes et objectifs des déplacements individuels. Les avantages et limites de ce type de donnée sont discutés dans le contexte des épidémies de dengue.
collection	OpenEdition Journal
language	Anglais
format	Article ou chapitre numérique
building	0/Bibliothèque numérique/ 1/Bibliothèque numérique/OpenEdition Journals/
topic	Twitter mobilité quotidienne Google POI Bangkok Twitter urban mobility Google POI Bangkok
spellingShingle	Twitter mobilité quotidienne Google POI Bangkok Twitter urban mobility Google POI Bangkok Cebeillac, Alexandre Daudé, Eric Huraux, Thomas Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
description	Human mobilities in urban areas have an impact on the spread of infectious diseases, including those caused by mosquito-borne diseases like dengue and Zika virus. Therefore, finding appropriate data and methods to perform spatial analyses of mobilities is a critical issue. The emergence of substantial amount of geolocated data, which is easily available on the Internet, has a great potential in mobility researches, especially when paired with land use, following the activity-space concept. This paper, focused on the dengue endemic mega-city of Bangkok (Thailand), explores the potentialities of (A) using a land use classification from Google’s points of interest (POIs) to assess the likelihood of performing an activity from (B) a large dataset of individual geolocated tweets to characterize and quantify daily mobility. These emerging data sources allow the characterization of (C) the rhythms of daily mobility in Bangkok, from the perspective of (1) the macroscopic urban pulse and (2) the rhythms and aims for individual movement. The advantages and limitations of this kind of data will be finally discussed regarding dengue epidemics.
author	Cebeillac, Alexandre Daudé, Eric Huraux, Thomas
author_facet	Cebeillac, Alexandre Daudé, Eric Huraux, Thomas
author_sort	Cebeillac, Alexandre
title	Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
title_short	Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
title_full	Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
title_fullStr	Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
title_full_unstemmed	Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?
title_sort	where ? when ? and how often ? what can we learn about daily urban mobilities from twitter data and google pois in bangkok (thailand) and which perspectives for dengue studies ?
publisher	Netcom
publishDate	2018
container_title	URI:https://journals.openedition.org/netcom
url	https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.4000/netcom.2725 https://ezproxy.univ-orleans.fr/login?url=https://journals.openedition.org/netcom/2725
_version_	1877242066415648768

Where ? When ? And how often ? What can we learn about daily urban mobilities from Twitter data and Google POIs in Bangkok (Thailand) and which perspectives for dengue studies ?

Registos relacionados