Recommender systems have been successfully used in electronic commerce applications such as recommending books, movies, restaurants and airlines based on users' past behaviour. More recently, such systems have made inroads into social media, for examples to recommend partners in online dating sites. In our work, we have developed a social behaviour based recommender system within an online community with the aim to increase the level of interactions in the community, thereby increasing its social capital (the density of interactions among its members in the community) and its chance of sustainability. Our recommender system is built on a social trust model. It is able to recommend people and content. Importantly, it can recommend people in different roles: friends, mentors and leaders. In this paper, we describe our context and the social behaviour based recommender system we developed.
|Number of pages||6|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2012|
- Online Communities
- Social Behaviour
- Social Trust