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　Reviewson Amazon
　　
　　亚马逊的评论
　　
　　Five-starfakes
　　
　　一流的伪造
　　
　　Theevolving fight against sham reviews
　　
　　与虚假评论的斗争正愈演愈烈　
　　
　　“I WILL post awesome review on your amazon product,”bess98 declared on Fiverr, a website where individuals sell freelance servicesfor $5 or more. On October 16th Amazon charged that bess98 and more than 1,000others were illegally hawking customer reviews. The case comes just six monthsafter Amazon sued the operator of four sites peddling similar stuff, includingthe subtly named buyamazonreviews.com.
　　
　　一个ID为“bess98”的人在五美元网站（Fiverr）宣称：“我能给您亚马逊的商品好评”，自由职业者可以在这个网站以五美元或者更高的价格来出售服务。在10月16日，亚马逊把bess98以及1000多名从事非法刷评的人员告上法庭。在这件事发生六个月之前亚马逊曾起诉了四家出现类似兜售服务的网站，这其中包括网站域名被巧妙命名为“buyamazonreviews.com”的网站
　　
　　LikeAmazon, other websites have fought fakes with lawsuits, carefully honedalrithms and even sting operations—Yelp, a popular review site, has hadundercover staff answer ads from firms seeking glowing write-ups. Yet theproblem persists.
　　
　　像亚马逊一样，其他网站也通过法律诉讼、完善网站算法甚至安排特情人员等途径来打击虚假评论。一家很受欢迎的评论网站Yelp已经安排卧底通过散发寻求刷评小广告的形式来打击虚假评论。但是商家买好评的行为仍然存在。
　　
　　Foras long as there have been online reviews, there have been fakes. Themotivation is clear: for example, one extra star on a restaurant’s Yelp ratingboosts revenue by 5-9%, according to Michael Luca of Harvard Business School.Mr Luca and Georgios Zervas of Boston University have shown that restaurantsseeking fake acclaim are likely to be independent—online reviews matter more tothem than to chains with established reputations. So some businesses askfriends to post raves, seek reviewers-for-hire and offer customers discounts inexchange for praise.
　　
　　从网评出现的时候，虚假评论就伴随而生。出现这种现象的动机很明确：例如，酒店在Yelp上的评级每提高一颗星，意味着其年营业额将会增长5%至9%。哈佛商学院的迈克尔卢卡（Michael Luca）称。卢卡先生和波士顿大学的乔治·泽瓦斯（Georgios Zervas）表明了酒店寻求虚假评论大概是因为获取独立的网络评论要比单纯的建立信誉链方法多的多。比如一些商家会通过朋友刷评、雇佣评论手或对乘客返现换好评的方式寻求好评。
　　
　　Forwebsites that claim to be an impartial resource, such practices are troubling. “Whilesmall in number,” Amazon contends in its new suit, “these reviews cansignificantly undermine the trust that consumers and the vast majority ofsellers and manufacturers place in Amazon.” The problem is particularly irksomefor sites dedicated to offering reviews, such as Yelp and TripAdvisor. Amazonsells everything from books to lawnmowers; Yelp’s main offerings are its 83mreviews. “If consumers can’t rely on the content,” says Vince Sollitto of Yelp,“then the service is of no value.”
　　
　　对于一个想要成为让客人放心的网站来说，这种事情是很麻烦的。“尽管数量少”，亚马逊在它的新诉讼中争论到，“这些评论可以轻而易举的破坏消费者和绝大多数卖家以及制造商寄予亚马逊的信任”这个问题就让Yelp和猫途这类致力于提供评论的网站变的非常讨厌。在亚马逊上销售的从书本到割草的所有商品，Yelp提供了大约八千三百万评论。“如果消费者不能信赖这些评论”， 文斯苏里说道，“那么这项服务将没有任何价值”。
　　
　　Sowebsites have tried to fight fakes. Alrithms comb reviews for suspiciouswording. Expedia allows hotel recommendations only by those who have paid for aroom there. Amazon tags a review as “verified” if the writer has indeed boughtthe product. Presumably such reviews are more reliable, though bess98 is one ofmany who claim to be able to game Amazon’s system.
　　
　　Yelpmay have the most aggressive strategy. An alrithm removes a whopping 30% ofposts from Yelp’s list of “recommended” reviews, though consumers can still seethe suspicious ones if they like. Businesses that try to weasel their way to ahigher rating (paying off grumpy clients, for instance) have their Yelp pagesbranded with a red warning.
　　
　　所以，网站已经在努力打击虚假评论。例如通过算法将可疑词汇过滤掉。艾派迪公司（（Expedia）主要经营商业服务和供应）只允许那些已经支付过房间费用的人发表推荐。如果读者已经确实买过产品，亚马逊就会将他标记为“已核实”。虽然很多包括像bess98在内的这类网站宣称可以将亚马逊的系统玩弄于鼓掌，但是据推测，通过这种方式处理过的评论变的可信的多。

  在Yelp上实行的或许是最有攻击性的策略了，一个算法清除了Yelp“推荐”评论列表中30%的评论。但如果顾客愿意的话，他们仍然可以看到那些有可疑词汇的评论。而有一些试图通过给暴脾气客户返现求好评来到达更高等级的商家已经被Yelp打上了警告标记。
　　
　　Despiteall this, some false acclaim and critiques inevitably slip past firms’defences. For websites, fake reviews will remain a stubborn headache. Meanwhilebusinesses are finding new ways to boost their reputations online. Socialbots—lines of code that pose as real accounts—can build buzz on social-mediasites like Twitter and Facebook. For the average consumer, it may become everharder to distinguish real praise from puff.
　　
　　尽管有了这些，一些虚假的好评和差评还是不可避免的突破了公司的防御。对于网络来说，虚假评论将仍是一个顽疾。同时商家还在网上在寻找能提高他们声誉新方法。随着科技的发展，由代码编制的社交机器人可以在例如推特和Facebook这类的社交媒体上留下类似真实的说话声。因此对于普通的顾客来说，从宣传广告中分辨真正的好评变得越来越困难。

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