An approach for opinion-demographic-topology based microblog friend recommendation
Sherin M. Moussa;
Abstract
Through the tremendous increase of users on the microblogging social networks with their associated streams of content, the scarcity of one user’s attention arises. The process of filtering such massive content and discovering who other users could be aligned with his own interests would consume much time. Thus, various mechanisms have been investigated to recommend friends by analyzing the posted content, social graph, or user profiles. In this paper, we propose a new approach for microblog friend recommendation based on the opinion, or sentiment, towards the topics in the microblogs combined with the social graph, in addition to the demographic data available in the user profiles, including age, gender, and location. We have deployed a cloud-based recommender service using R language for big data analytics, which applies our proposed approach to gather feedback from real Twitter users. Results show 0.77 average precision value, with 21 % increase rate considering opinion mining.
Other data
Title | An approach for opinion-demographic-topology based microblog friend recommendation | Authors | Sherin M. Moussa | Keywords | Big data analytics;Sentiment analysis;Topic models;Social graph;Twitter;Social network;Recommender system;Opinion mining | Issue Date | 1-Jan-2017 | Publisher | SPRINGER INTERNATIONAL PUBLISHING AG | Journal | Advances in Intelligent Systems and Computing | Volume | 533 | Start page | 815 | End page | 824 | ISBN | 9783319483078 | ISSN | 21945357 | DOI | 10.1007/978-3-319-48308-5_78 | Scopus ID | 2-s2.0-84994514639 | Web of science ID | WOS:000398724000078 |
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