LoTrust: A social Trust Level model based on time-aware social interactions and interests similarity

Abstract

OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18269 Abstract-With the immense growth of online social applications, trust plays a more and more important role in connecting users to each other, sharing their personal information and attracting him to receive recommendations. Therefore, how to obtain trust relationships through mining online social networks became a critical issue. To calculate the level of trust between two users, many computational trust models are proposed which mainly rely on the social network structure, the explicit trust from user to another, the users' behaviors, or the users' similarity, etc. However, the majority of these models ignored the temporal factor. In this paper, we propose a trust relationship detection mechanism from an egocentric social network in order to compute the trust level between an active user and his directed friends. We propose a Level of social Trust model, that we called LoTrust, which is suitable for personalized recommendation purpose. This computational model founded on novel trust metric which is based not only on the users' interests similarity according to their semantic social profiles (RDF/FOAF), but also takes into account the time factor of the users' active interactions (e.g comments, share photo, wall posts, messages). We perform experiments on real life dataset extracted from Facebook. The experimental results demonstrated how our LoTrust model produces satisfactory results than other computational models.

Rating Prediction Algorithm Based on User Time-Sensitivity

“…Taking into account the impact of time, Frikha et al [26] proposed to integrate the temporal factor in measuring trust between social network friends and developed a Trusted Friends' Facebook application to demonstrate the importance of time in users' interactions for determining social trusted friends. Kalaï et al [27] proposed a level of social trust model, which is founded on novel trust metrics based not only on the users' interests similarity according to their semantic social profiles but also takes into account the time factor of the users' active interactions. The experimental results demonstrated how their model produces satisfactory results than other computational models.…”

Social collaborative service recommendation approach based on user’s trust and domain-specific expertise

“…Level of trust computing. We proposed in this step to compute for each active user the trust value based on novel metric, called Level of trust metric (LoT), that we defined in [34]. This metric allows to discriminate between trusted and untrusted friends from egocentric network.…”

“…Hence, this matrix is very sparse and it becomes difficult to compare two users and calculate the similarity between them. However, in our work, we propose to compute the trust level by taking into account other impact factors like the users' social interactions [34].…”

Modeling Computational Trust Based on Interaction Experience and Reputation With User Interests in Social Network

“…(ii) Models exploiting contexts of intereraction among peers such as tags, comments or user's profiles on social networks to estimate trustworthiness among users. These data resources are utilized to determine uer's interests, similarity as well as relationship between peers [4,15];…”

“…(iii) Hybrid models combining interaction scores and degrees of interests or similarity of users [4,6].…”