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'Make New Friends, but Keep the Old' - Recommending People on Social Networking Sites

机译:“结交新朋友,但保持旧的” - 推荐社交网站上的人

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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 social networking site using a personalized survey of 500 users and a field study of 3,000 users. We found all algorithms effective in expanding users' friend lists. Algorithms based on social network information were able to produce better-received recommendations and find more known contacts for users, while algorithms using similarity of user-created content were stronger in discovering new friends. We also collected qualitative feedback from our survey users and draw several meaningful design implications.
机译:本文研究人们建议旨在帮助用户找到已知的,离线联系人,并在社交网站上发现新朋友。我们使用500个用户的个性化调查和3,000名用户的实地考察,在企业社交网站中评估了四个推荐人算法。我们发现所有有效扩展用户朋友列表的算法。基于社交网络信息的算法能够生成更好地接收的建议,并找到更了解用户的已知联系人,而使用用户创建的内容的相似性的算法在发现新朋友时更加强大。我们还收集了我们的调查用户的定性反馈,并提取了几种有意义的设计含义。

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