假新闻传播路线图：特朗普当选全靠俄罗斯段子手？

目前，围绕着假新闻在何种程度上帮助特朗普赢得了竞选的争论仍在发酵，很多人都认为互联网上存在着一个松散的右翼网站联盟，它就是通过各个社交网络平台大量转发这些假新闻的主要推手。猜测归猜测，却很少有人尝试使用科学的方法去探究这一问题。

北卡罗来纳州伊隆大学教授乔纳森·奥尔布莱特是一名数据新闻领域的专家，曾为谷歌和雅虎工作过，主要从事媒体分析和社交网络方面的研究。近日，他围绕互联网上的假新闻生态系统绘制了一张“假新闻传播路线图”。

由于Facebook和谷歌的巨大体量，它们当之无愧地成为了假新闻最大的两个传播途径。不过奥尔布莱特的研究却以科学的方法使我们得以一览这些传播途径背后的假新闻供应链。或许这将有助于我们理解谁才是炮制假新闻的最大推手，以及他们的目的究竟是什么。

奥尔布莱特表示，他的研究方法首先是考察某些最大的假新闻传播站点的网络访问量。奥尔布莱特在发表于medium.com上的一篇文章中指出，即便谷歌和Facebook决定禁止假新闻网站使用他们的广告网络，但仍不足以解决假新闻泛滥的问题。

奥尔布莱特指出，这是由于大量进出这些网站的访问量都是有机地实现的。而这些假新闻网站之所以在谷歌的搜索引擎和Facebook的动态消息里排在前面，也是由于这个原因。很多假新闻的传播是通过各个老式网站之间的共享实现的。也就是说，它们是通过电子邮件发送的。

这也促使奥尔布莱特更深入地进行了访问量分析和社交网络绘图工作。他想确定哪些大网站吸引了最多的访问量，以及它们又通过Facebook和Twitter等社交网络与其他哪些网站产生了联系。奥尔布莱特在文中这样写道：

“谷歌的广告网络和Facebook的最新动态所使用的‘相关文章’算法，会放大假新闻给人带来的情感冲击，而社交媒体天生就具有放大政治戾气的能力。不过我认为，不论是新闻记者、研究人员还是数据专家，他们首先应该关注：1、与内容生产有的因素；2、与网络访问量有关的因素。”

接下来，奥尔布莱特进行了一轮“中等规模的数据分析”，探索分析了117个已知的与假新闻有关的网站。随后他发表了一篇名叫《2016美国大选微宣传机器》(The #Election2016 Micro-Propaganda Machine)的文章，通过图表指出了这些网站之间的联系。并且根据它们之间的联系的强弱，将这它们画成了以下大小不一的圆点。

As debate continues over the extent to which “fake news” helped Donald Trump win the presidential race, many have talked about a network of loosely-affiliated, right-wing sites that distributed this content through social media platforms. But few have tried to describe it in scientific terms.

Jonathan Albright, a professor at Elon University in North Carolina, is an expert in data journalism who has worked for both Google and Yahoo. He specializes in media analytics and social networks, and he has created a network map or topology that describes the landscape of the fake-news ecosystem.

Even if Facebook and Google are the largest distributors of fake news or disinformation because of their size, Albright’s work arguably provides a scientifically-based overview of the supply chain underneath that distribution system. And that could help determine who the largest players are and what their purpose is.

Albright says his research started with a look at the traffic generated by some of the top fake-news distribution sites. As he described in a post published on Medium, he came to the conclusion that banning them from ad networks run by Google or Facebook wouldn’t solve the problem.

That’s because much of the traffic to and from those sites—and therefore their presence at the top of Google’s search engine or high up in the Facebook news feed—is achieved organically, he argued. Many seemed to be driven primarily by sharing through old-fashioned networks. In other words: they’re sent via email.

This led Albright deeper into the traffic-analysis and social mapping process. He tried to determine which of the top sites were driving the most traffic and who else they were connected to via Facebook and Twitter. As Albright described it:

Google’s ad network and Facebook’s News Feed/“Related Stories” algorithms amplify the emotional spread of misinformation, and social media naturally turn up the volume of political outrage [but] I think journalists, researchers and data geeks should first look into the factors that are actually 1) producing the content and 2) driving the online traffic.

Next Albright did what he called a “medium-scale data analysis,” crawling and indexing 117 websites that are known to be associated with fake news. In a follow-up post, entitled The #Election2016 Micro-Propaganda Machine, he mapped the connections between those sites and plotted them as dots, based on the strength of their connections.

随后，奥尔布莱特又将他的样本扩展到了300多个网站，其中包括布莱巴特新闻网（Breitbart News）等一些知名的新闻传播渠道。他总共收集分析了130多万个进出这些网站的外链。

第一眼看见奥尔布莱特的这张网络地图，很多人都会产生这样一种印象，即有些“节点”或“枢纽”推动了大量与假新闻有关的访问量。但图中也有数量极多的网站是不少人说不定连听都没听说过的。

在奥尔布莱特发现的两个最大的“枢纽”中，其中之一是一个名叫“保守百科”(Conservapedia)的网站——它相当于是左翼版的维基百科，另一个网站名叫Rense，这两者都吸引了大量的访问流量。这张图上其他比较知名的节点还包括布莱巴特新闻网、每日传讯（DailyCaller）和YouTube等等。（有些假新闻网站可能想通过YouTube这个渠道利用他们的访问量赚钱。）

奥尔布莱特表示，他特别注意不去深究到底是什么人炮制了这些假新闻。不过《华盛顿邮报》最近发表的一篇报道引述了一个没有什么名气的团体的说法，称炮制这波假新闻的幕后黑手是一个俄罗斯的行动网络——不过这则分析并非很有说服力。

奥尔布莱特表示，他只是想了解一下这个问题的波及面，以及各个假新闻的生产基地和传播网站之间是如何互相联系的。奥尔布莱特还想用公开数据和开源工具来进行这项研究，这样其他人也能构建出类似的模型。他表示：

“在查无实据或证据不全的情况下主张一条新闻是‘假新闻’，这并不是最好的做法——实际上它可能是最糟糕的策略，因为它进一步加剧了当前的喧嚣。最近，我觉得很多记者和新闻机构都是在针对大众的反应‘制造’新闻，而不是先行一步地解读那些根本性的问题。”

有了以上这张假新闻生态系统的“地图”，人们就能明白各个假新闻传播节点之间的联系，而谷歌、Facebook等大型社交平台以及其他媒体机构也就能更容易地追踪假新闻的蔓延势头，提出可能的解决方案。（财富中文网）

译者：朴成奎

Albright subsequently expanded his sample to include more than 300 sites, including some prominent distributors such as Breitbart News. In total, he collected and analyzed the incoming and outgoing traffic of more than 1.3 million URLs.

More than anything, the impression one gets from looking at Albright’s network map is that there are some extremely powerful “nodes” or hubs that propel a lot of the traffic involving fake news. And it also shows an entire universe of sites that many people have probably never heard of.

Two of the largest hubs Albright found were a site called Conservapedia—a kind of Wikipedia for the right wing—and another called Rense, both of which got huge amounts of incoming traffic. Other prominent destinations were sites like Breitbart News, DailyCaller and YouTube (the latter possibly as an attempt to monetize their traffic).

Albright said he specifically stayed away from trying to determine what or who is behind the rise of fake news. The Washington Post recently wrote about a report from a little-known group that says a network of Russian actors are behind the wave, although the analysis was fairly weak.

Instead, Albright said he just wanted to try and get a handle on the scope of the problem, as well as a sense of how the various fake-news distribution or creation sites are inter-connected. Albright also wanted to do so with publicly-available data and open-source tools so others could build on it. He said:

Reporting on ‘fake news’ with unsubstantiated claims and incomplete evidence isn’t the best approach—in fact, it’s probably the worst strategy, because it adds to the existing noise. Lately, I feel that many journalists and news organizations are churning out news in response to the public, rather than leading the way to inform them on the underlying issues.

With the landscape of the fake-news ecosystem outlined in terms of the connections between the various nodes, it may be easier for platforms like Google and Facebook—or even for other media outlets—to track the spread of the problem and come up with potential solutions.