Categorizing events using spatio-temporal and user features from Flickr

Abstract

We introduce a method for discovering the semantic type of events extracted from Flickr, focusing in particular on how this type is influenced by the spatio-temporal grounding of the event, the profile of its attendees, and the semantic type of the venue and other entities which are associated with the event.

Étudier les représentations des paysages sur les réseaux sociaux

“…Aurélien Allouche 1 Les sites Internet de partage de photographies sont l'objet, depuis peu, d'études de grande ampleur destinées à éclairer les pratiques de consommation du territoire et des espaces naturels (Donaire et al, 2014 ;Van Canneyt et al, 2016 ;Yuan et Medel, 2016). Ils apparaissent ainsi à la recherche comme une source privilégiée de données de taille importante pour l'étude des perceptions de l'environnement et des paysages (Cord et al, 2015 ;Dunkel, 2015 ;Knochel, 2013).…”

Categorizing events using spatio-temporal and user features from Flickr

“…The hypothesis we consider in this paper is that in many cases the event type can be discovered by looking at characteristics, such as timing, the location of the event or properties of attendees, which can be readily obtained from social media sources. For example, when an event occurs on a Saturday inside a sport * A full version [1] of this paper has been accepted and will be published (Jan. 2016) in Information Sciences. complex and it has basketball players as main actors, it is very likely that this event is of type 'basketball game'.…”

Traveller‐generated destination image: Analysing Flickr photos of 193 countries worldwide

“…Tourists tend to take more photos of famous landmarks and downtown areas than residents, who are more interested in cultural and recreational attractions (D. Li et al, 2018). Due to the pervasiveness, breadth, and popularity of the platform, much recent research has used Flickr photos for various purposes, such as assessing people's emotions in a city (Ashkezari-Toussi, Kamel, & Sadoghi-Yazdi, 2019), classifying events in a city (Van Canneyt, Schockaert, & Dhoedt, 2016), comparing DI among tourists (Deng et al, 2019), identifying the DI (Galí & Donaire, 2015), and detecting tourist activities (Nechita, Demeter, Briciu, Varelas, & Kavoura, 2019).…”