专栏名称: 考研英语时事阅读
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51好读  ›  专栏  ›  考研英语时事阅读

【经济学人】大数据时代的到来|2017.05.25|总第923期

考研英语时事阅读  · 公众号  · 考研  · 2017-07-17 05:56

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导读


大数据时代的到来给我们提供许多有用且便利的信息 ,通过大量数据的收集整理和分析,电脑得出普遍的结论,基于这些,我们可以更加有针对性的选择自己客户对象,减少虚假目标对象。

Truth and statistics

真相和统计数据

How to find out what people really think

如何找出人们的真正想法

Data mining is becoming more and more precise

数据挖掘技术的结果变得越来越精确

May 25th 2017

Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. By Seth Stephens-Davidowitz. Dey Street; 288 pages; $27.99. To be published in Britain by Bloomsbury in July; £20.

每个人都在撒谎:大数据,新数据,以及互联网能告诉我们什么是真实的自己。Seth Stephens Davidowitz撰写《他们的街道》,该书共288页;27.99美元。于7月在英国的布卢姆斯伯里出版社出版,每本20英镑。


TO MANY people Big Data is less shiny than it was a year ago. After Hillary Clinton’s defeat at the hands of Donald Trump, her vaunted analytics team took much of the blame for failing to spot warnings in the midwestern states that cost her the presidency. But according to research by Seth Stephens-Davidowitz, a former data scientist at Google, Mrs Clinton’s real mistake was not to rely too much on newfangled statistics, but rather too little.

对很多人来说,大数据没有一年前那么耀眼。希拉里·克林顿败在唐纳德·特朗普手后,她自负的分析团队有很大的责任,因为他没有注意中西部州的情况,使她失去了总统位置。但据曾在谷歌工作的数据科学家Seth Stephens Davidowitz的研究,克林顿的失误不是过于依赖新奇的数据,而是么有关注这些数据。

  • Vaunted 吹嘘,夸耀

  • Newfangled 新奇的


Mrs Clinton used the finest number-crunchers. But their calculations still relied largely on traditional sources, such as voter files and polls. In contrast, Mr Stephens-Davidowitz turned to a novel form of data: Google searches. In particular, he counted the frequency of queries for the word “nigger”, America’s most toxic racial slur. Contrary to the popular perception that overt racism is limited to the South, the numbers showed comparatively high interest in the term across the Midwest and the rustbelt relative to the rest of the country. In the Republican primaries in 2016 that variable outperformed all others in predicting which geographic areas would support Mr Trump over his intraparty rivals.(读者试译) Had Mrs Clinton’s team made better use of such information, they might have concluded, before it was too late, that the foundations of her “blue firewall” were cracking.

克林顿用的数字处理器是最好的。但他们的计算仍然依赖于传统的来源,如选民文件和民意调查。相比之下,Stephens Davidowitz用了一种新数据的形式:谷歌搜索。特别是,他统计查询美国最毒的种族歧视的词“黑鬼”的频率 。(期待您的翻译,明天将会有针对这句话的长难句解析哟~)如果克林顿的团队更好地利用这些信息,他们可能会得出结论,在为时已晚之前,她的“蓝色防火墙”正在开裂。

  • Number-crunchers 数字处理器

  • Rustbelt衰退地区

  • Outperformed 胜过

  • Intraparty 政党内的


This is just one of the striking findings in “Everybody Lies”, a whirlwind tour of the modern human psyche using search data as its guide. Some of the book’s discoveries reaffirm conventional wisdom, like the concentration of queries about do-it-yourself abortions and about men who are confused about their sexual orientation in America’s socially conservative South. Some turn it on its head: although rags-to-riches narratives are widespread in basketball, the data show that growing up in poverty actually reduces a boy’s chances of making the National Basketball Association—perhaps because poor children are less likely to grow tall enough to play in it. Some results are both disturbing and perplexing, such as the prevalence of searches on pornographic sites for videos depicting sexual violence against women, and the fact that women themselves seek out these scenes at least twice as often as men do. Other results are just weird: why are adult men in India so eager to have their wives breastfeed them?

这只是“人人谎言”的惊人发现之一,它是以搜索数据为导向的现代人类心理的旋风之旅。这本书的一些发现重申了传统的智慧,比如关注主动堕胎质疑,以及在美国保守的南部一些对于自己性取向感到困惑的男人。有些人会这样想:虽然在篮球运动中普遍存在着“白手起家”的说法,但数据显示,在贫困中成长的男孩实际上减少了男孩进入国家篮球协会的机会,可能是因为贫穷的孩子身高不太高,么有达到可以参加篮球比赛的高度。一些结果令人不安,费解,比如色情网站上搜索对女性进行性暴力视频的盛行,而事实上,女性自己搜索的频率至少是男性的两倍。其他的结果也很奇怪:为什么印度的成年男性如此渴望妻子的母乳喂养?

  • Psyche 灵魂

  • Reaffirm 重申,再肯定

  • Rags-to-riches 白手起家的

  • Prevalence 盛行

  • Pornographic 色情的

  • Breastfeed 哺乳


The empirical findings in “Everybody Lies” are so intriguing that the book would be a page-turner even if it were structured as a mere laundry list. But Mr Stephens-Davidowitz also puts forward a deft argument: the web will revolutionise social science just as the microscope and telescope transformed the natural sciences.

“每个人的谎言”中的研究结果很有趣,尽管这本书像是一个洗衣单但Stephens Davidowitz先生也提出了一个巧妙的说法:互联网将彻底改变社会科学就像显微镜和望远镜改变了自然科学。

  • Empirical 凭经验的

  • Revolutionise 使彻底变革

Modern microeconomics, sociology, political science and quantitative psychology all depend to a large extent on surveys of at most a few thousand respondents. In contrast, he says, there are “four unique powers of Big Data”: it provides new sources of information, such as pornographic searches; it captures what people actually do or think, rather than what they choose to tell pollsters; it enables researchers to home in on and compare demographic or geographic subsets; and it allows for speedy randomised controlled trials that demonstrate not just correlation but causality. As a result, he predicts, “the days of academics devoting months to recruiting a small number of undergraduates to perform a single test will come to an end.” In their place, “the social and behavioural sciences are most definitely going to scale,” and the conclusions researchers will be able to reach are “the stuff of science, not pseudoscience”.

现代微观经济学、社会学、政治学和定量心理学在很大程度上取决于对几千名受访者的调查。相反,他说,“大数据”有四个独特的能力:大数据会提供新的信息来源,如色情搜索;它抓住了人们所做所想,而不是他们选择告诉民意调查者的内容;研究人员能够在家比较人口或地理亚群;它可以快速进行随机对照试验不仅可以证明相关关系,也可以证明因果关系因此,他预测,“学者夜以继日致力于招收少量学生进行测试的日子就要结束。”从这一点来看,“社会和行为科学无疑会规模化”研究人员得出的结论是科学,而不是伪科学。

  • Pollsters 民意调查者

  • Demographic 人口统计的

  • Pseudoscience 伪科学


Mr Stephens-Davidowitz is not just any knee-jerk cheerleader for the Big Data revolution. He devotes ample space both to the ways that quantitative findings can lead decision-makers astray, and to the risk that the nearly omniscient owners of such data sets may find ways to abuse them. If liking motorcycles turns out to predict a lower IQ, he asks, should employers be allowed to reject job applicants who admit to liking motorcycles? As a result, he calls for extreme caution in extending the use of Big Data from large groups of people to making decisions about individuals. On the whole, however, the author is an optimist. As a result of improvements in information technology, he writes, humans will “be able to learn a lot more” about themselves “in a lot less time”.

Stephens Davidowitz先生不只是对大数据革命下意识地实验。他大量投入研究定量的结果可能导致决策者误入歧途,以及那些几乎无所不知的数据拥有者可能会找到滥用数据的方法。他问,如果喜欢摩托车能预测低智商,雇主是否应该拒绝接受喜欢摩托车的求职者?其结果是,他呼吁在扩大大数据的使用过程中,要谨慎地做出决策。但总的来说,作者是乐观的。他写道,由于信息技术的进步,人类能够“在更短的时间内”更多地了解自己。

  • Knee-jerk 膝反射的,下意识的

  • Omniscient 无所不知的


翻译 ▍小小

审核 ▍小太阳Kiki

图文编辑 ▍毛毛

责任编辑 ▍毛毛

Try to translate 

In the Republican primaries in 2016 that variable outperformed all others in predicting which geographic areas would support Mr Trump over his intraparty rivals.

Put Chinese below

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