搜索的社会化转向编辑本段回目录
当下，即便在互联网上，重要的不是你知道什么而是你认识谁。
After a decade when search engines ruled supreme — tapping billions of Web pages to answer every conceivable query — many people now prefer getting their online information the old-fashioned way: by yakking across the fence.
搜索引擎长达十年的极权统治——弹出数十亿个网页以答复无所不包的查询——之后，许多人宁可用老套的方式获取信息：在小圈子里高谈阔论。
Turning to friends is the new rage in the Web world, extending far beyond established social networking sites and setting off a rush among Web companies looking for ways to help people capitalize on the wisdom of their social circles — and to make some money in the process.
谈到朋友是网络世界的新风潮，远远超越既有的社交网络，并带动了那些寻求将社交圈中的智慧资本化的公司蜂拥进入这一领域——同时在这个过程中挣些钱。
“What your friends think and what people like you think is much more relevant than what everybody thinks,” said Augie Ray, an analyst with Forrester Research.
弗洛斯特研究中心研究员奥格·雷说，“朋友所想与同类所想比起人人所想更具关联度。”
Amazon.com now allows its shoppers to connect to their Facebook accounts so that Amazon can display their friends’ favorite books, films and other products. TunerFish, a start-up owned by Comcast, lets users share what television shows and movies they are watching, mapping out an up-to-the-minute TV guide of programs gaining in popularity among their friends.
如今，亚马逊允许网购者链接到他们的脸谱帐户中以便亚马逊展示其好友所钟意的书籍、电影及其他产品。康卡斯特旗下新启动的网站TunerFish让用户分享他们正在看的电视剧以及电影、制定最新的电视节目收视向导以此帮助他们在朋友圈里获得好感。
And Loopt, a location-focused social network with 3.4 million registered users, recently began showing them which of their friends liked a particular restaurant.
而拥有340万注册用户的在地社交网站Loopt最近开始为用户们展示其朋友所喜欢的独特的餐馆。
“We’ve gotten a tremendous response from that,” said Sam Altman, a co-founder. Mr. Altman said that one’s network of friends “is an incredible predictor of what you will like.”
“我们因此获得了强烈的反响，”网站创始人之一山姆 阿尔特曼说一个人的朋友网络“是你个人喜好的绝佳预言者。”
On Google and other search engines, searches for things like hotels or electronics can turn up a lot of online clutter and spam. Instead, many people informally poll their friends for recommendations, often through social networks like Facebook and Twitter.
在谷歌或者其他搜索引擎里，搜索旅馆或者电子产品时很可能得到的是一大堆杂乱的网上信息及垃圾邮件。相反的是，许多人常常会非正式地通过脸谱或者推特之类的社交网站、在自己的朋友中做调查以获得他们的建议。
“Improving search has always been about improving relevance,” Mr. Ray of Forrester said. “But the thinking now is that getting information from your immediate social network is what will really make results more relevant.”
弗洛斯特研究中心的雷先生说，“优化搜索就意味着提升关联度。但现在的理念是从最直接的社交圈中获得信息代表着所得到的结果更具相关性。”
While user-contributed review sites like Yelp and TripAdvisor have long been popular ways to get a quick reading on a new place to eat, the sheer volume of reviews they offer can be overwhelming.
尽管Yelp及TripAdvisor之类的用户提交型评测网站早就是人们很快找个新地方吃饭的颇受欢迎的途径，但数量庞大的评测意见很可能是令人窒息的。
And the reliability of those reviews can be hard to gauge. Some may have been planted by management, while others are from disgruntled customers with a bone to pick.
同时，这些评测意见的可靠性也难以判断。有些很可能是经营者策划的，而有些则是那些不好伺侍候的主儿在鸡蛋里头挑骨头。
The trust factor of friends’ suggestions can make a big difference. Mr. Altman said Loopt’s users are 20 times more likely to click on a place their friends had liked or visited than a place that simply ranked higher in search results.
朋友建议中的信任因素则可能令结果完全不同。阿尔特曼先生说，Loopt的用户点击朋友喜欢或者浏览过的网页的次数，比点击搜索结果中排名靠前的网页的次数高出20倍！
So-called recommendation engines on sites like Amazon and Netflix try to guess what customers might like by comparing their previous purchases or rentals with those of others with similar tastes. But that approach often does not offer much insight as to why a particular film or restaurant is being recommended, said John Riedl, a professor of computer science at the University of Minnesota.
亚马逊及Netflix之类所谓的推荐引擎试图通过就顾客曾经的购买及租赁行为与其品味相近的其他人进行比较，以此来估测他们的喜好。明尼苏达大学计算机科学教授约翰·雷德尔说，这样的办法常常无法就为什么某部特定电影或者餐馆会备受推崇给出多少有见地的看法。
Social networks, he said, “do a richer job of constructing recommendations.” For example, seeing that a friend is frequenting a new pizzeria can have a lot of influence over whether you go.
他说，社交网络“在形成推荐上做得更富成效。”比如，看到一个朋友老是光顾某家新的比萨饼店，可能对你是否跟进产生很大的作用。
Of course, your friends are not generating the amount of data that a company like Amazon may use to make its automated recommendations, which could result in fewer choices. “The trade-off is that you will be more comfortable with the recommendation,” Mr. Riedl said.
诚然，你的朋友们无法生成足够多的、象亚马逊这样的公司用来形成自动推荐的数据，这会导致有限的选项。雷德尔先生说，“两相权衡之下你会对所获得（朋友）的推荐更加满意。”
TV watching, often a solitary activity, is an obvious candidate for some social tips. TunerFish shows which programs are gaining in popularity in your online social circle, and what is being watched right now.
通常作为个体活动的看电视显然是某种社交窍门的备选项。TunerFish会显示你的线上社交圈里哪个节目正在流行，又有哪个节目大家正在收看。
Although TunerFish is available only on the Web for now, the company says it could eventually be brought to the TV screen through an application running on a set-top box.
尽管TunerFish提供的这些服务眼下只能在网上使用，但这个公司说它最终将可以通过在借助机顶盒上运行程序使这些功能在电视上实现。
Facebook has its own recommendation system in place. The service allows its 500 million members to click a button to indicate what news articles, companies and celebrities they “like,” and it shares data about those preferences with its Web partners. When a Facebook user visits a Web site like Yelp or TripAdvisor, they are shown reviews from friends before they get to those from strangers.
脸谱自己的推荐系统也已准备就绪。这项服务允许其5亿用户点击某个按键以展示他们所“喜欢”的新闻、公司及名人，并与其网上拍档分享他们各自的偏好资料。当某个脸谱用户访问Yelp 或TripAdvisor之类的网站，他首先看到的是朋友的评价而不是陌生人的评价。
Facebook recently began introducing a feature called Facebook Questions that allows users to pose questions to friends and strangers using the site. Last month it introduced a service called Places that encourages people to “check in” at places they visit and broadcast their location to friends.
脸谱最近开始引入一允许用户向使用该网站的朋友及陌生人提出问题的所谓“脸谱问答”的功能。上个月，它还启用一个被称为“定位”的服务、鼓励人们在他们造访的地点登录网站并给好友播报其位置。
The new services will help Facebook amass even more data on its users’ tastes. But for now there is no comprehensive way to search through or refer back to the information your friends have shared.
新的服务有助于脸谱积累更多的用户偏好的数据。不过，至今仍没有一种全面的方式可以探知或者查阅你的朋友已经分享了你的哪些信息。
Bret Taylor, the chief technology officer at Facebook, said the company’s main focus was on helping other sites add social features. But he said the company was thinking about ways to corral the “likes” and suggestions of its members into a more cohesive system.
脸谱首席技术官布拉特· 泰勒称该公司的正集中力量帮助其他网站增加社交功能。但他说该公司正在研究将用户的“喜好”与建议归集于一个更有凝聚力的系统之中。
“Exposing higher-quality recommendations in more obvious and prominent ways would improve the health of the system,” he said.
“以更加显而易见及更突显出的方式来展示高质量的推荐意见，将改善这个系统的健康，”他说。
Hunch, a start-up based in New York, wants to go beyond cataloging the places and products for which your friends have already expressed affection. With some complex software, it tries to use that information to predict what other things you might like, even if nobody you know has ever offered an opinion on those things before.The service pulls in data about articles, topics and people that you and your friends have “liked” on Facebook or follow on Twitter. “Based on your placement in the social graph and who your friends are, we can make inferences about what you like,” said Chris Dixon, who founded the company with Caterina Fake, one of the creators of Flickr.
纽约市一家新公司Hunch想走得更远，不只是对好友喜欢的场所及产品进行目录编入。借助一些复杂的软件，它试图利用这些信息对你可能还喜欢的其他事情进行预测，即便此前尚未有任何人对这些事物发表过评论。
这项服务引入脸谱或者推特上你和你的朋友对所“喜欢”及跟贴的文章和话题相关的数据。“基于你在社会图谱中的位置以及你的朋友圈，我们就可以推断你的喜好，”与卡特里娜·费克一起创办这家公司克里斯·迪克森如是说，他也是 Flickr的创立者之一。
For example, Hunch’s database shows that people who are big fans of Twitter are also likely to be interested in visiting the Museum of Modern Art in New York, while the non-Twitterati tend to favor the theater.
比如，Hunch的数据库表明推特的狂热粉丝同样很可能对参观纽约的当代艺术博物馆很感兴趣，而对推特不感冒的人则倾向偏爱戏院。
Mr. Dixon said the company was testing a local search tool that can make restaurant, shopping and hotel recommendations. “We can take your taste profile and data from the Web and begin to match you to places that you will like,” he said.
迪克森先生称该公司正在测试一款可以给出餐饮、购物及住宿推荐的在地搜索工具。他说，“我们可以从网上获取你的爱好情况与数据，并着手让你与你所喜欢的地方相匹配。”
The company says it plans to unveil partnerships with major e-commerce, news and travel sites, along with mobile location-based services.
该公司称它计划开启与主要的电子商务、新闻及旅行网站一道进行移动定位服务方面的合作。
A shopping or travel site that Hunch is working with could help a visitor decide which offerings would best suit their tastes. Based on the data Hunch has collected about correlations between user preferences, the site might suggest that someone in search of a hotel in Las Vegas should stay at the Venetian if her online circle of friends listens to hip-hop artists like Rihanna and Usher.
与Hunch合作的购物或者旅行网站可能有助于访问者就哪一种选择更适合他们的品味做出决定。基于Hunch已经收集的有关用户与偏好之间相关性的数据，网站就可以建议想在拉斯维加斯过夜的人可以选择待在 Venetian酒店，如果她线上的朋友圈喜欢听Rihanna 和Usher等嘻哈音乐歌手的歌。
The friend trend, where likes matter more than links, could eventually present a significant challenge to Google, which has struggled to create appealing social services.
同好比联系更重要意味着友人倾向可能会慢慢变成谷歌的重大挑战，尽管它正努力打造一些有吸引力的社交服务。
In February the company introduced Buzz, which lets Gmail users share updates and photos, and it is including those updates in its customized results when users perform Web searches.
今年二月，该公司引入了Buzz服务，它让Gmail用户得以分享他们的更新与照片，它还包括用户使用网页搜索时所订制内容的更新。
“People are likely to find what your friends are saying about the iPhone 4 or a Chinese restaurant more helpful in a Web search,” said Matt Cutts, a software engineer who oversees search quality at Google.
“人们有可能发现好友关iPhone 4或者某家中餐馆的议论在网页搜索中会更有帮助，”谷歌负责监管搜索质量的软件工程师马特·库特思说。
Mr. Cutts declined to talk about what Google might do next in the social search area, but he did say he expected “these sorts of trends to continue.”
库特思不肯透露谷歌在社交搜索领域的下一步作为，但他肯定地说他希望“这些趋势将会持续下去。”
