In this paper, we propose a novel data model for Multimedia Social Networks, i.e. particular social media networks that combine information on users belonging to one or more social communities together with the content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and represent in a simple way all the different kinds of relationships that are typical of social media networks, and in particular among users and multimedia content. We also introduce some user and multimedia ranking functions to enable different applications. Finally, some experiments concerning effectiveness of the approach for supporting relevant information retrieval activities are reported and discussed.
Sentiment analysis on yelp social network / Amato, Flora; Colace, Francesco; Cozzolino, Giovanni; Moscato, Vincenzo; Picariello, Antonio; Sperlì, Giancarlo. - (2017), pp. 99-106. (Intervento presentato al convegno 23rd International Conference on Distributed Multimedia Systems, Visual Languages and Sentient Systems, DMSVLSS 2017 tenutosi a Pittsburgh, United States nel 7-8 July, 2017) [10.18293/DMSVLSS2017-014].
Sentiment analysis on yelp social network
Flora Amato;Giovanni Cozzolino;Vincenzo Moscato;Antonio Picariello;Giancarlo Sperlì
2017
Abstract
In this paper, we propose a novel data model for Multimedia Social Networks, i.e. particular social media networks that combine information on users belonging to one or more social communities together with the content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and represent in a simple way all the different kinds of relationships that are typical of social media networks, and in particular among users and multimedia content. We also introduce some user and multimedia ranking functions to enable different applications. Finally, some experiments concerning effectiveness of the approach for supporting relevant information retrieval activities are reported and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.