SMORE: Towards a semantic modeling for knowledge representation on social media

• A Semantic MOdeling REpresentation for extracted information of social networks is presented.
• The model can be used by an RS that allows the generation of multi-domain recommendations.
• The model is not restricted to working in a single domain.
• The model has been evaluated with extracted semantic data from Twitter.

This research presents SMORE, a semantic model for knowledge representation on social media. In order to provide recommendations, the model provides the elements for representing the content through the use of an ontological model and semantic techniques for the characterization and relationships between user profiles, products and social networks. In fact, with this model could be the basis of recommendation system based on social media data, and it could be exploited use by the recommendations on different products, which are stored in the Web and with similar characteristics between them. Moreover, SMORE represent the information related to user of the social networks in order to have a user characterization to be used for future recommendations in several domains. The semantic model has been evaluated with semantic data extracted from a trusted social network as, Twitter, obtaining the information specified by an expert in the field of marketing for recommendations in the automotive industry.