Towards a dynamic and polarity-aware social user profile modeling

The emergence of social networks and the communication facilities they offer have generated an enormous informational mass. This social content is used in several research and industrial works and has had a great impact in different processes. In this paper, we present an overview of social information use in Information Retrieval (IR) and Recommendation systems. We first describe several user profile models using social information. A special attention is given to the following points: the analysis of the different user profiling models incorporating social content in Information Retrieval (IR) and in social recommendation methods. We distinguish between the models using social signals and relations, and the models using temporal information. We also present current and future challenges and research directions to enhance IR and recommendation process. We then describe our proposed model of social polarized and temporal user profile building and use in social recommendation context. Our proposal tries to address open challenges and establish a new model of user profile that fits information needs in recommender systems.

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