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            "title": "Web 2.0 geotagged photos: assessing the spatial dimension of the phenomenon",
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                    "firstName": "Vyron",
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            "abstractNote": "Among popular Web 2.0 applications are the social networking, photo-sharing websites like Flickr,\nPanoramio, Picasa Web, and Geograph. The phenomenon of user-generated content and the increased presence\nof geographic information in such applications have motivated researchers to consider them as a\nsource of geographic information. In this paper we question whether such web applications can serve as\nreliable sources of spatial content. We differentiate between spatially explicit and implicit applications, in\naccordance to their declared aims, and evaluate if they have an impact on the spatial distribution of geotagged\nphotos for Great Britain. We also compare the spatial distribution of the photos submitted with population\ndata, and the patterns of contribution to these sources over a period of 18 months. Finally, at a larger scale,\nwe examine the spatial distribution of photos and their spatial density for 15 test areas and look into issues\nsuch as data currency and user behaviour. Our findings show that only web applications that urge users to\ninteract directly with spatial entities can serve as reliable, universal sources of spatial content.\n1. Introduction\nThe advances in the technologies associated\nwith the World Wide Web (the Web) over the past\nfew years have been significant, leading to the identification\nof a step change in web technologies that is\ntermed Web 2.0. While users contributed to the Web\nin its early days, Web 2.0 users are now central to the\nprocess of creating, sharing, consuming and disseminating\ninformation. This bi-directional flow of\ninformation leads to the growth in user-generated\ncontent (UGC). UGC has also affected the delivery\nof Geographic Information (GI) on the Web. By\ntoday’s standard, the majority of web maps around\n2005 had a very basic and trivial form. Today, common\nusers and experts interact and publish spatial\ninformation using sophisticated web mapping services\nranging from Google Maps, Microsoft’s Bing\nMaps, or Yahoo! Maps, through to Virtual Globes\nlike Google Earth or NASA’s World Wind.\nThe growth of UGC opens up new opportunities\nfor mapping the world. As Goodchild [2007b] states,\nthe arguments made by Estes and Mooneyhan\n[1994], about a mistaken popular notion of a wellmapped\nworld, are still true. In fact, mapping and\nmap updating programs are suffering serious delays\nin many countries due to budget limitations and\nrapid development. Thus, in the area of GI, it seems\nthat UGC opens up the possibility of supplying\ninformation that can be used to update and maintain\nexisting databases. The core question that is raised\nby this suggestion is, how effective is this data for\nupdating existing spatial information databases?\nResearchers have acknowledged the fact that\nthe evolution of the Web and the maturation of certain\nenabling technologies, such as Javascript\nApplication Programming Interfaces (APIs), GPSGEOMATICA\nVol. 64, No. 1, 2010 pp. 99 to 110\nVyron Antoniou\nJeremy Morley\nMordechai Haklay\nParmi les applications Web 2.0 populaires, nous avons accès aux sites Web de réseautage social et de\npartage de photos comme Flickr, Panoramio, Picasa Web et Geograph. Le phénomène du contenu généré par\nl’utilisateur et la présence accrue de l’information géographique dans ces applications ont motivé les\nchercheurs à les considérer comme source d’information géographique. Dans le présent article, nous tentons\nde déterminer si de telles applications Web peuvent servir de sources fiables de contenu spatial. Nous faisons\nla différence entre les applications spatialement explicites et implicites, conformément à leurs buts déclarés.\nNous évaluons aussi si ceci a une incidence sur la distribution spatiale des photos avec balise géographique\n(géotag) pour la Grande-Bretagne. De plus, nous comparons la distribution spatiale des photos soumises avec\nles données sur la population et les modèles de contribution à ces sources sur une période de 18 mois. Enfin,\nà plus grande échelle, nous examinons la distribution spatiale des photos et leur densité spatiale pour 15\nrégions d’essai et évaluons des questions telles que l’actualité des données et le comportement des utilisateurs.\nNos constatations démontrent que seules les applications Web qui incitent les utilisateurs à interagir\ndirectement avec les entités spatiales peuvent servir de sources universelles fiables de contenu spatial.",
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            "note": "<p>Le projet de Peter Warden était d'analyser les données tirées de 210 millions de profils publics.</p>\n<p>Il produit une carte de 7 grandes régions des Etats-Unis construits à partir des lieux regroupant les connexions les plus fréquentes. Il caractérise ces régions en fonction des fan pages dominantes des profils. La méthodologie de hiérarchisation des liaisons et de segmentation des régions est rien moins que clair.Les limites et la typologie sont fantaisistes et semblent refléter les a priori de l'auteur.</p>\n<blockquote>\n<p>With that in mind, I took a screenshot of my city analysis, grabbed <a href=\"/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/jar:file://mce_host/../../../../zotero.jar%21/content/zotero/tinymce/note.html\">SumoPaint</a> and started sketching in the patterns I'd noticed. 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Warden est un ancien ingénieur de chez Apple qui s'est mis à son compte sur le marché de l'analyse et de la visualisation des données du Web : messagerie, Twitter. Son idée était de \"crawler\" (indexer ou récupérer les données d'un serveur) sur les profils de Facebook. Il avait fait la même chose sur Google. Il a donc écrit son propre programme et l'a laissé tourner 6 mois. Il a aussi écrit un programme permettant de cartographier la fréquence de localisation aux Etats-Unis des Page Fan de Facebook. L'objectif était explicitement de développer des outils de marketing. Sur Fanpage Analytics on trouve une carte des liaisons entre cité et Etats des Etats-unis et pays du Monde.</p>\n<p>L'annonce qu'il allait mettre à la disposition de tous ses données&nbsp; a conduit Facebook à le menacer d'un procès. 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            "note": "<p><strong>Projet :</strong> Création d'images pour une série de 131 villes dans le monde  présentant les lieux photographiés à partir des photos publiés sur  Flickr et sur Picasa en distinguant celles prises par les \"touristes\" et  celles prises par les \"locaux\"  <br /> Lieu : Paris     <br /> Méthodologie : La distinction entre photographies de touristes et  photographies de locaux n'est pas tirée du lieu d'habitation de  l'utilisateur de Flickr, qui est facultatif dans le profil et non  publiée sur le Web. Elle est inférée de la période couverte par les  photographies de l'auteur dans la même ville: si elle est de 1 mois ou  plus, le photographe est réputé être un local (points bleus), si elle  est de moins d'un mois ce serait un touriste (points rouges). Les points  jaunes sont indéterminés. Ce sont des personnes ayant pris des  photographies un peu partout pendant plus d'un mois. D'après l'auteur,il  s'agit vraisemblablement de touristes mais peut être aussi des  personnes publiant peu de photographies. La localisation des points est  tirée des Géotags des photographies. Les traits relient deux photos  prises à 10 mn d'intervalle. Les cartes sont dans des projections  cylindriques spécifiques avec l'échelle des latitude et longitude égales  au point central. Les régions représentées sont toutes à la même  échelle (15 miles Est-Ouest). L'extraction se fait grâce aux API Flickr  et Picasa. Le fond de carte est Open Street Map.</p>\n<p>Quelques remarques à caractère méthodologique tirées des commentaires sur le  site :  <br /> - établir en complément d'autres distinctions : photographies prises  le week-end / durant la semaine, entre 9 h. du soir et 3 h. du matin  pour cartographier la vie nocturne, analyser le niveau de luminosité et  la balance des couleurs pour voir où vont les gens selon qu'il fait beau  ou non ...  <br /> - il peut y a voir un biais lié au fait que les  personnes ne géolocalisent pas ou ne publient pas sur Flickr les photos  qu'ils prennent près de chez eux pour des raisons de vie privé. Le  volume des photographies des résidents est certainement sous-estimé.  <br /> - ne serait-il pas possible de faire une visualisation présentant la  proportion de touristes et de locaux plutôt que de superposer les deux  phénomènes ? Par exemple en appliquant une grille sur la carte et en  calculant les % par cellule.  <br /> - le choix d'une projection  cylindrique spécifique à chaque lieu peut créer certaines distorsions  dans les hautes latitudes mais surtout ne facilite pas la superposition à  Google Maps ou l'intégration dans un SIG. <br /> <br /> Quelques remarques sur les usages : <br /> - Certains commentateurs envisagent d'utiliser ces cartes pour prendre des photographies là où \"les locaux\" en prennent.</p>",
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