Nowadays, since social media sites and online social networks have created big media data, it is thus complex and time-consuming for users to find the preferred social media from a large media catalog. Social media recommender systems are therefore emerged to recommend personalized media objects. However, most media recommender systems only focus on one aspect of social media. It is lacking a big picture of how to build an effective social media recommender system. Therefore, this paper tackles this challenge first for specifying the distinct features of media object that can be used for recommender systems, and then discusses five critical aspects that can affect the design of social media recommender systems. This paper further indicates how to assemble these critical aspects and concludes that when we apply traditional recommender algorithms in the media context, those are the critical aspects to improve and optimize social media recommneder systems.

Factoring Personalization in Social Media Recommendations

Persia, F
2019-01-01

Abstract

Nowadays, since social media sites and online social networks have created big media data, it is thus complex and time-consuming for users to find the preferred social media from a large media catalog. Social media recommender systems are therefore emerged to recommend personalized media objects. However, most media recommender systems only focus on one aspect of social media. It is lacking a big picture of how to build an effective social media recommender system. Therefore, this paper tackles this challenge first for specifying the distinct features of media object that can be used for recommender systems, and then discusses five critical aspects that can affect the design of social media recommender systems. This paper further indicates how to assemble these critical aspects and concludes that when we apply traditional recommender algorithms in the media context, those are the critical aspects to improve and optimize social media recommneder systems.
File in questo prodotto:
File Dimensione Formato  
fact.pdf

solo utenti autorizzati

Descrizione: Articolo principale
Tipologia: Documento in Versione Editoriale
Licenza: Creative commons
Dimensione 132.48 kB
Formato Adobe PDF
132.48 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/166630
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 3
social impact