劍橋商務(wù)英語BEC高級(jí)閱讀基礎(chǔ)練習(xí)
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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.
一項(xiàng)覆蓋面廣的學(xué)術(shù)研究報(bào)告表明，電腦程序可以通過跟蹤人們?nèi)绾问褂肍acebook網(wǎng)站，來獲取越來越多的個(gè)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.
這項(xiàng)報(bào)告顯示，電腦程序可以識(shí)別Facebook用戶的性別、服藥習(xí)慣、甚至這些用戶年幼時(shí)父母是否離婚等私人信息。
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.
在這次研究中，來自大學(xué)心理測(cè)驗(yàn)團(tuán)隊(duì)和微軟公司(Microsoft)資助的一家研究中心的.科學(xué)家們共同分析了5.8萬名Facebook用戶的數(shù)據(jù)，以推測(cè)其個(gè)人資料中并未提供的個(gè)人特征和其他信息。在同類研究中，這是規(guī)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.
這一算法在推測(cè)男性性傾向、種族、以及宗教和政治傾向的準(zhǔn)確度分別為88%、95%和80%。在個(gè)性類型以及情緒穩(wěn)定性方面，該算法的推測(cè)準(zhǔn)確度在62%到75%之間。Facebook拒絕對(duì)這一結(jié)果置評(píng)。
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.
這一研究凸顯出人們對(duì)于社交網(wǎng)絡(luò)以及通過挖掘數(shù)據(jù)特征獲取敏感信息的擔(dān)憂日益加深。即便在人們?cè)噲D對(duì)個(gè)人信息保密的情況下，通過挖掘數(shù)據(jù)特征也能獲得敏感信息。比如說，被推測(cè)為同性戀者的用戶中只有不到5%的人與同性戀團(tuán)體有聯(lián)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.”
該報(bào)告的作者之一邁克爾•科辛柯西(Michal Kosinksi)告訴英國《金融時(shí)報(bào)》，該大學(xué)的技術(shù)可以很容易地被公司用于同樣的目的——推斷人們不愿與人分享的個(gè)人特征，比如性取向或政治觀點(diǎn)。他表示：“我們使用的是十分簡(jiǎn)單而通用的方法。營銷公司與互聯(lián)網(wǎng)公司在這方面可能會(huì)花費(fèi)更多時(shí)間和資源，因此它們所獲信息的準(zhǔn)確度比我們更高。”
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.
該報(bào)告還揭示出一些出人意料的相關(guān)性。比如說喜歡“彈簧薯?xiàng)l(curly fries)”的人智商更高，而喜歡一個(gè)名為“穿著襪子在地板上滑(Sliding on Floors With Your Socks On)”的頁面的人不太可能吸食毒品。
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