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社交网络的流行对用户的隐私保护提出了新的挑战。该文通过使用人类动力学和统计物理的方法,研究用户的网络行为与用户隐私量值的关系。以当前国内流行的社交网络——人人网和新浪微博——为研究对象,获取用户的真实数据,提出隐私量化模型。研究结果表明:用户的网络行为对隐私量值具有重要的影响,如在人人网中用户的地理位置分享行为对隐私量值影响较大,而在新浪微博中发私信行为对隐私量值的影响最大。研究的结果对社交网络隐私关注下的用户行为规律探讨具有理论与实际意义。
The popularity of social networks poses new challenges for users’ privacy protection. This paper studies the relationship between the user’s network behavior and the value of user privacy through the use of human dynamics and statistical physics. Taking the current domestic popular social networks - Renren and Sina Weibo - as the research object, the real data of users are obtained and the privacy quantification model is proposed. The results show that the user’s network behavior has an important impact on the value of privacy, for example, the sharing behavior of users in the network has a greater impact on the amount of privacy, while in Sina Weibo, The greatest impact. The results of this study have theoretical and practical significance for exploring the rules of users’ behavior under the social privacy concerns.