When Diversity Meets Speciality: Friend Recommendation in Online Social Networks
نویسندگان
چکیده
Online social networks improve social experience by connecting users with common interests. Similar to real life, seeking good friends is much easier with recommendations in online social networks. In this paper, we investigate a series of problems related to friendship formation in the hope of improving friend recommendation in social networks. Specially, we seek to understand whether users who contribute more are more popular among other users, whether users like to make friends with popular users and the role difference of users with different diversity of individual interests in friendship formation. We propose a novel approach based on topic modeling to characterize the interest diversity degree of each user. The interest diversity features are used to help predict friend relationships between users. The experimental results on three large-scale datasets demonstrate the effectiveness of our method.
منابع مشابه
Mining Overlapping Communities in Real-world Networks Based on Extended Modularity Gain
Detecting communities plays a vital role in studying group level patterns of a social network and it can be helpful in developing several recommendation systems such as movie recommendation, book recommendation, friend recommendation and so on. Most of the community detection algorithms can detect disjoint communities only, but in the real time scenario, a node can be a member of more than one ...
متن کاملA Profile-based Friend Detection Scheme for Online Social Networks
In past few years, users created friends with every other World Health Organization live or work near them, like neighbor or work place etc. this kind of friendly relationship is named as ancient means of constructing friends or G. Friend referred to as geographical primarily based friends .Now social networking services recommend friends to users based on their social graphs, which may not be ...
متن کاملFriend Grouping Algorithms for Online Social Networks: Preference, Bias, and Implications
Managing friendship relationships in social media is challenging due to the growing number of people in online social networks (OSNs). To deal with this challenge, OSNs’ users may rely on manually grouping friends with personally meaningful labels. However, manual grouping can become burdensome when users have to create multiple groups for various purposes such as privacy control, selective sha...
متن کاملLeveraging Social and Content-based Recommendation in P2P Systems
We focus on peer-to-peer (P2P) content recommendation for on-line communities, where social relationships between users can be exploited as a parameter to increase the trust of recommendation. Most of the existing solutions establish friendship relationships based on users behavior or declared trust. In this paper, we propose a novel P2P recommendation approach (called F2Frec) that leverages co...
متن کاملPrivacy-Preserving and Efficient Friend Recommendation in Online Social Networks
The popularity of online social networks (OSNs) is on constant rise due to various advantages, including online communication and sharing information of interest among friends. It is often that users want to make new friends to expand their social connections as well as to obtain information from a broad range of people. Friend recommendation is a very important application in many OSNs and has...
متن کامل