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A market for social-media data Sippingfrom the fire hose
社交媒体数据的市场 细品弱水三千
Making sense of a torrent of tweets
从推文的洪流中找寻意义
MOST tweets are inane, but a million may contain valuable information.
多数推文单看起来没有什么重要意义，但是一百万条一起就可能含有价值不菲的信息。
Fed through clever algorithms, a torrent of microblogs can reveal changes in a nation smood.
通过聪明的算法，微博的洪流可以揭露一个国家的情绪变化。
Hence the excitement about a new market: the sale and analysis of real-time social-mediadata.
于是，对于一个新兴市场社交媒体数据实时销售和分析的兴奋就产生了。
DataSift, a start-up, will soon launch a marketplace for such information.
DataSift是一家创业型企业，它不久将推出一个针对这样的信息的市场。
Analysing social media used to be a cottage industry.
社交媒体的数据分析曾经是家庭作坊式的小本生意。
Firms gathered data slowly and patchily, through mechanisms not built for the purpose.
企业从非专属渠道缓慢而零散的收集数据。
Many online services kept their data locked up, because there was no way to make moneyfrom them. All this is changing.
很多在线服务商将它们的数据束之高阁，因为以前没有方法可以从中谋利。所有的这一切都在改变。
Twitter was the first to move because it generates ever more data: the number of tweets perday now exceeds 230m, up more than 100% from the beginning of the year.
推特是先行者，因为它产生了如此多的数据：每天有超过2.3亿条推产生，比年初多一倍多。
Twitter would like to turn its popularity into money, but rather than beefing up its owninfrastructure, it plans to outsource the task of distributing and selling its data to DataSift andGnip, another start-up.
推特希望把它的人气变成现金，但它并没有增加自己的基础设施建设，而是计划把分配和出售数据的任务外包给DataSift和Gnip。
Both DataSift and Gnip are striving to be data platforms .
DataSift 和Gnip都在为成为 数据平台 而努力。
They collect and standardise information from all kinds of social-media servicesnot onlyTwitter, but also Facebook, YouTube and others.
它们从各种社交媒体服务不仅是推特，也包括脸书，YouTube和其他收集、整理信息并使其标准化。
Both Gnip and DataSift have built robust networks which can cope with massive amounts ofdata in real time.
Gnip和DataSift都已经建立可靠网络用以对付实时的大规模数据。
And both are enforcing licensing rules: for instance, that a stream of tweets can be analysedbut not republished.
两家也都在实施许可规则：比如，一系列的推文可以用来分析，但是不能再次将其发布。
Gnip, based in Boulder, Colorado, is more of a wholesale distributor. It charges $33,000 amonth for a feed of half of all tweets.
位于科罗拉多的博尔德的Gnip公司更大程度上是一个批发型分销商。
Customers can also subscribe to feeds of tweets containing web links or certain keywords.
订阅全部推文的一半的消息源，要收3.3万美元每月。
Buyers are mostly social-media monitoring companies, which analyse the data for a fee.
客户也可以订阅包含网址或某些特定关键字的消息源。
Sysomos, a Canadian firm, for example, allows firms to track in real time what people thinkabout certain products.
买方通常是社交媒体监控企业，它们靠分析数据收费赚钱。例如，Sysomos是一个加拿大公司，它可以让企业实时追踪人们对于特定产品的感受。
DataSift serves both big corporations and individuals.
DataSift的服务对象包括大企业和个人。
Customers can define sophisticated filters, for instance to find all tweets by men who areinterested in a new product and live in London.
客户可以定义复杂的过滤条件，例如找到对一个新产品有兴趣，且在伦敦生活的男性所发的所有推文。
Charges for DataSift depend on the filter s complexity and the amount of data delivered.
DataSift的费用取决于过滤条件的复杂程度和交付的数据流量。
The streams from Gnip and DataSift can be combined with data from more specialised firmsthat try to extract meaning from social-media data.
Gnip和DataSift的数据流可以与更专业的企业的数据结合，那些更专业的企业试图从社交媒体数据中提取出意义。
Lexalytics, for instance, analyses the sentiment of messages and posts.
比如，Lexalytics分析消息和帖子的情绪。
Klout measures the influence of social-media users .
Klout则测量社交媒体用户的影响力。
Having a marketplace such as DataSift has already encouraged other social-media servicesto open their data vaults, says Nick Halstead, the founder of DataSift.
DataSift的创始人尼克?霍尔斯特德说，有了像DataSift那样的数据交易市场，使得更多的社交媒体服务商开启其数据的仓库。
Financial firms have become interested in feeding such data into the algorithms they use tomake investment decisions, says Chris Moody, Gnip s president.
Gnip的总裁克里斯?穆迪说，金融企业对此也有兴趣：将这样的数据放到他们的算法里，来做出投资决策。
And corporations are increasingly keen on combining social-media data with customerinformation.
企业越来越热衷于将社交媒体数据和客户信息相结合。
Yet growth in this market could be held backby privacy concerns.
然而，对于隐私的担忧可能会阻碍这个市场的发展。
Most people think that tweets are only up to 140 characters long.
多数人认为一条推文最多只有140个字符那么长。
But those who sip from Twitter s fire hose can get much more information, including asender s location, the biography on his profile page and how many people have subscribedto his messages .
但是那些从推特的数据洪流中 细细品味 的人，可以从中得到更多的信息，包括发送者的所在位置，从个人介绍页面得到的档案信息，以及有多少人订阅了他的信息。
Most of this information is freely available on Twitter s website.
多数这样的信息都是可以从推特的网站上免费获取的。
But if users realise how their data are used, they may clam up.
但是，一旦用户意识到他们的数据是怎样被使用的，他们可能就会缄口不言了。
A market for social-media data Sippingfrom the fire hose
社交媒体数据的市场 细品弱水三千
Making sense of a torrent of tweets
从推文的洪流中找寻意义
MOST tweets are inane, but a million may contain valuable information.
多数推文单看起来没有什么重要意义，但是一百万条一起就可能含有价值不菲的信息。
Fed through clever algorithms, a torrent of microblogs can reveal changes in a nation smood.
通过聪明的算法，微博的洪流可以揭露一个国家的情绪变化。
Hence the excitement about a new market: the sale and analysis of real-time social-mediadata.
于是，对于一个新兴市场社交媒体数据实时销售和分析的兴奋就产生了。
DataSift, a start-up, will soon launch a marketplace for such information.
DataSift是一家创业型企业，它不久将推出一个针对这样的信息的市场。
Analysing social media used to be a cottage industry.
社交媒体的数据分析曾经是家庭作坊式的小本生意。
Firms gathered data slowly and patchily, through mechanisms not built for the purpose.
企业从非专属渠道缓慢而零散的收集数据。
Many online services kept their data locked up, because there was no way to make moneyfrom them. All this is changing.
很多在线服务商将它们的数据束之高阁，因为以前没有方法可以从中谋利。所有的这一切都在改变。
Twitter was the first to move because it generates ever more data: the number of tweets perday now exceeds 230m, up more than 100% from the beginning of the year.
推特是先行者，因为它产生了如此多的数据：每天有超过2.3亿条推产生，比年初多一倍多。
Twitter would like to turn its popularity into money, but rather than beefing up its owninfrastructure, it plans to outsource the task of distributing and selling its data to DataSift andGnip, another start-up.
推特希望把它的人气变成现金，但它并没有增加自己的基础设施建设，而是计划把分配和出售数据的任务外包给DataSift和Gnip。
Both DataSift and Gnip are striving to be data platforms .
DataSift 和Gnip都在为成为 数据平台 而努力。
They collect and standardise information from all kinds of social-media servicesnot onlyTwitter, but also Facebook, YouTube and others.
它们从各种社交媒体服务不仅是推特，也包括脸书，YouTube和其他收集、整理信息并使其标准化。
Both Gnip and DataSift have built robust networks which can cope with massive amounts ofdata in real time.
Gnip和DataSift都已经建立可靠网络用以对付实时的大规模数据。
And both are enforcing licensing rules: for instance, that a stream of tweets can be analysedbut not republished.
两家也都在实施许可规则：比如，一系列的推文可以用来分析，但是不能再次将其发布。
Gnip, based in Boulder, Colorado, is more of a wholesale distributor. It charges $33,000 amonth for a feed of half of all tweets.
位于科罗拉多的博尔德的Gnip公司更大程度上是一个批发型分销商。
Customers can also subscribe to feeds of tweets containing web links or certain keywords.
订阅全部推文的一半的消息源，要收3.3万美元每月。
Buyers are mostly social-media monitoring companies, which analyse the data for a fee.
客户也可以订阅包含网址或某些特定关键字的消息源。
Sysomos, a Canadian firm, for example, allows firms to track in real time what people thinkabout certain products.
买方通常是社交媒体监控企业，它们靠分析数据收费赚钱。例如，Sysomos是一个加拿大公司，它可以让企业实时追踪人们对于特定产品的感受。
DataSift serves both big corporations and individuals.
DataSift的服务对象包括大企业和个人。
Customers can define sophisticated filters, for instance to find all tweets by men who areinterested in a new product and live in London.
客户可以定义复杂的过滤条件，例如找到对一个新产品有兴趣，且在伦敦生活的男性所发的所有推文。
Charges for DataSift depend on the filter s complexity and the amount of data delivered.
DataSift的费用取决于过滤条件的复杂程度和交付的数据流量。
The streams from Gnip and DataSift can be combined with data from more specialised firmsthat try to extract meaning from social-media data.
Gnip和DataSift的数据流可以与更专业的企业的数据结合，那些更专业的企业试图从社交媒体数据中提取出意义。
Lexalytics, for instance, analyses the sentiment of messages and posts.
比如，Lexalytics分析消息和帖子的情绪。
Klout measures the influence of social-media users .
Klout则测量社交媒体用户的影响力。
Having a marketplace such as DataSift has already encouraged other social-media servicesto open their data vaults, says Nick Halstead, the founder of DataSift.
DataSift的创始人尼克?霍尔斯特德说，有了像DataSift那样的数据交易市场，使得更多的社交媒体服务商开启其数据的仓库。
Financial firms have become interested in feeding such data into the algorithms they use tomake investment decisions, says Chris Moody, Gnip s president.
Gnip的总裁克里斯?穆迪说，金融企业对此也有兴趣：将这样的数据放到他们的算法里，来做出投资决策。
And corporations are increasingly keen on combining social-media data with customerinformation.
企业越来越热衷于将社交媒体数据和客户信息相结合。
Yet growth in this market could be held backby privacy concerns.
然而，对于隐私的担忧可能会阻碍这个市场的发展。
Most people think that tweets are only up to 140 characters long.
多数人认为一条推文最多只有140个字符那么长。
But those who sip from Twitter s fire hose can get much more information, including asender s location, the biography on his profile page and how many people have subscribedto his messages .
但是那些从推特的数据洪流中 细细品味 的人，可以从中得到更多的信息，包括发送者的所在位置，从个人介绍页面得到的档案信息，以及有多少人订阅了他的信息。
Most of this information is freely available on Twitter s website.
多数这样的信息都是可以从推特的网站上免费获取的。
But if users realise how their data are used, they may clam up.
但是，一旦用户意识到他们的数据是怎样被使用的，他们可能就会缄口不言了。
