The increasing amount of personal information that can be gleaned by computer programs that track how people use Facebook has been revealed by an extensive academic study.
一项覆盖面广的学术研究报告表明，电脑程序可以通过跟踪人们如何使用Facebook网站，来获取越来越多的个人信息。

Such programs can discern undisclosed private information such as Facebook users’ sexuality, drug-use habits and even whether their parents separated when they were young, according to the study by the University of Cambridge academics.
这项报告显示，电脑程序可以识别Facebook用户的性别、服药习惯、甚至这些用户年幼时父母是否离婚等私人信息。

In one of the biggest studies of its kind, scientists from the university’s psychometrics team and a Microsoft-funded research centre analysed data from 58,000 Facebook users to predict traits and other information that were not provided in their profiles.
在这次研究中，来自大学心理测验团队和微软公司(Microsoft)资助的一家研究中心的科学家们共同分析了5.8万名Facebook用户的数据，以推测其个人资料中并未提供的个人特征和其他信息。在同类研究中，这是规模最大的研究之一。

The algorithms were 88 per cent accurate in predicting male sexual orientation, 95 per cent for race and 80 per cent for religion and political leanings. Personality types and emotional stability were also predicted with accuracy ranging from 62-75 per cent.
这一算法在推测男性性倾向、种族、以及宗教和政治倾向的准确度分别为88%、95%和80%。在个性类型以及情绪稳定性方面，该算法的推测准确度在62%到75%之间。Facebook拒绝对这一结果置评。 

The study highlights growing concerns about social networks and how data trails can be mined for sensitive information, even when people attempt to keep information about themselves private. Less than 5 per cent of users predicted to be gay, for example, were connected with explicitly gay groups.
这一研究凸显出人们对于社交网络以及通过挖掘数据特征获取敏感信息的担忧日益加深。即便在人们试图对个人信息保密的情况下，通过挖掘数据特征也能获得敏感信息。比如说，被推测为同性恋者的用户中只有不到5%的人与同性恋团体有联系。

Michal Kosinksi, one of the report’s authors, told the Financial Times that the university’s techniques could easily be replicated by companies to infer personal attributes a person did not wish to share, such as sexual orientation or political views: “We used very simple and generic methods. Marketing companies and internet companies could spend much more time and resources, and hence get much higher accuracy than we did.” 
该报告的作者之一迈克尔•科辛柯西(Michal Kosinksi)告诉英国《金融时报》，该大学的技术可以很容易地被公司用于同样的目的——推断人们不愿与人分享的个人特征，比如性取向或政治观点。他表示：“我们使用的是十分简单而通用的方法。营销公司与互联网公司在这方面可能会花费更多时间和资源，因此它们所获信息的准确度比我们更高。”  

The report also revealed some unexpected correlations – such as people who liked ‘curly fries’ having higher IQs, while those who like Facebook’s “Sliding on Floors With Your Socks On” page were unlikely to use drugs. 
该报告还揭示出一些出人意料的相关性。比如说喜欢“弹簧薯条(curly fries)”的人智商更高，而喜欢一个名为“穿着袜子在地板上滑(Sliding on Floors With Your Socks On)”的页面的人不太可能吸食毒品。 

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