Towards Psychometrics-Based Friend Recommendations in Social Networking Services

Felix Beierle, Kai Grunert, Sebastian Göndör, Viktor Schlüter
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引用次数: 10

Abstract

Two of the defining elements of Social Networking Services are the social profile, containing information about the user, and the social graph, containing information about the connections between users. Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph. In this paper, we argue that psychometrics, the field of measuring personality traits, can help make meaningful friend recommendations based on an extended social profile containing collected smartphone sensor data. This will support the development of highly distributed Social Networking Services without central knowledge of the social graph.
社交网络服务中基于心理测量学的朋友推荐
社交网络服务的两个定义元素是包含用户信息的社交概要和包含用户之间联系信息的社交图。社交网络服务用于与已知的人建立联系,也用于发现新的联系人。目前的好友推荐机制主要利用社交图谱。在本文中,我们认为心理测量学,即测量人格特质的领域,可以帮助基于包含收集的智能手机传感器数据的扩展社交档案做出有意义的朋友推荐。这将支持高度分布式的社交网络服务的发展,而无需社交图谱的核心知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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