Make new friends, but keep the old: recommending people on social networking sites
作者： Jilin Chen , Werner Geyer , Casey Dugan , Michael Muller , Ido Guy
关键词: Recommender system 、 Similarity (psychology) 、 Computer science 、 Field (computer science) 、 World Wide Web 、 Social network 、 Internet privacy
摘要: This paper studies people recommendations designed to help users find known, offline contacts and discover new friends on social networking sites. We evaluated four recommender algorithms in an enterprise site using a personalized survey of 500 field study 3,000 users. found all effective expanding users' friend lists. Algorithms based network information were able produce better-received more known for users, while similarity user-created content stronger discovering friends. also collected qualitative feedback from our draw several meaningful design implications.
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