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虚假信息是如何在网上传播的?

更新时间:2018-3-15 21:06:35 来源:纽约时报中文网 作者:佚名

How Lies Spread Online
虚假信息是如何在网上传播的?

The spread of misinformation on social media is an alarming phenomenon that scientists have yet to fully understand. While the data show that false claims are increasing online, most studies have analyzed only small samples or the spread of individual fake stories.

社交媒体上虚假信息的传播是一个令人担忧的现象,科学家们对此尚未完全了解。虽然数据表明,网上的虚假陈述在增加,但大多数研究只分析了少量样本或个别虚假故事的传播。

My colleagues Soroush Vosoughi, Deb Roy and I set out to change that. We recently analyzed the diffusion of all of the major true and false stories that spread on Twitter from its inception in 2006 to 2017. Our data included approximately 126,000 Twitter “cascades” (unbroken chains of retweets with a common, singular origin) involving stories spread by three million people more than four and a half million times.

我和同事苏鲁什·沃索吉(Soroush Vosoughi)以及黛布·罗伊(Deb Roy)打算改变这种状况。前不久,我们分析了从2006年到2017年在Twitter上流传的所有重要真实和虚假故事从诞生起的传播情况。我们的数据包括Twitter上的约12.6万个“瀑布”(有单一起源、未被打断的转发链),涉及被300万人转发了450万次的一些故事。

Disturbingly, we found that false stories spread significantly more than did true ones. Our findings were published on Thursday in the journal Science.

令人不安的是,我们发现,虚假故事比真实故事传播得更广。我们的研究结果发表在周四的《科学》(Science)杂志上。

We started by identifying thousands of true and false stories, using information from six independent fact-checking organizations, including Snopes, PolitiFact and Factcheck.org. These organizations exhibited considerable agreement — between 95 percent and 98 percent — on the truth or falsity of these stories.

我们首先采用Snopes、PolitiFact和Factcheck.org等六个独立事实核查机构的信息找出了数千个真实和虚假的故事。这些机构对这些故事真实与否的判断表现出高度的一致——在95%到98%之间。

Then we searched Twitter for mentions of these stories, followed the sharing activity to the “origin” tweets (the first mention of a story on Twitter) and traced all the retweet cascades from every origin tweet. We then analyzed how they spread online.

然后,我们在Twitter上搜索这些故事被提及的情况,跟随转发活动找到“起源”推文(也就是Twitter上第一次提到这个故事的帖子),从每一个起源推文那里开始追踪所有的转发活动。然后,我们分析了它们是如何在网上传播的。

For all categories of information — politics, entertainment, business and so on — we found that false stories spread significantly farther, faster and more broadly than did true ones. Falsehoods were 70 percent more likely to be retweeted, even when controlling for the age of the original tweeter’s account, its activity level, the number of its followers and followees, and whether Twitter had verified the account as genuine. These effects were more pronounced for false political stories than for any other type of false news.

我们发现,不管是哪类信息——政治、娱乐或商业等——虚假的故事都比真实的故事传播得更远、更快、更广。即使是在控制了起源Twitter账号所有者的年龄、账号活跃度、粉丝数量和关注数量,以及Twitter是否验证了账号真实性等因素之后,虚假信息被转发的可能性仍比真实信息多70%。虚假政治故事被转发的可能性超过任何其他类型的虚假故事。

Surprisingly, Twitter users who spread false stories had, on average, significantly fewer followers, followed significantly fewer people, were significantly less active on Twitter, were verified as genuine by Twitter significantly less often and had been on Twitter for significantly less time than were Twitter users who spread true stories. Falsehood diffused farther and faster despite these seeming shortcomings.

令人惊讶的是,平均而言,与传播真实故事的Twitter用户相比,散布虚假故事的Twitter用户的粉丝数量明显更少,关注的人也明显更少,在Twitter上的活跃度明显更低,被Twitter验证为真实账户的比例更低,开始使用Twitter的时间明显更短。尽管存在这些表面上的不利之处,虚假故事依然散布得更远、更快。

And despite concerns about the role of web robots in spreading false stories, we found that human behavior contributed more to the differential spread of truth and falsity than bots did. Using established bot-detection algorithms, we found that bots accelerated the spread of true stories at approximately the same rate as they accelerated the spread of false stories, implying that false stories spread more than true ones as a result of human activity.

尽管人们对网络机器人在传播虚假故事方面的作用感到担忧,但我们发现,在真实故事和虚假故事的传播差异方面,人类行为的作用大于机器人。我们通过使用现有的机器人检测算法发现,机器人在加速真实故事和虚假故事的传播速度方面大致是一样的,这意味着,虚假故事比真实故事传播得更广是人类活动的结果。

Why would that be? One explanation is novelty. Perhaps the novelty of false stories attracts human attention and encourages sharing, conveying status on sharers who seem more “in the know.”

为什么会这样呢?一个原因是新奇感。虚假故事的新奇感也许能吸引人类的注意力,刺激他们进行转发,以表明分享者似乎“消息更灵通”。

Our analysis seemed to bear out this hypothesis. Using accepted computerized methods for inferring emotional content from word use, we found that false stories inspired replies on Twitter expressing greater surprise than did true stories. The truth, on the other hand, inspired more joy and trust. Such emotions may shed light on what inspires people to share false stories.

我们的分析似乎证实了这种假设。我们使用可信的电脑手段,从词语推断使用者的情绪感受,最终发现,与真实故事相比,虚假故事在Twitter上引发的回复传达出更多的惊讶情绪。另一方面,真实故事激发的情绪更多是欢乐和信任。这些情绪也许有助于解释激发人们转发虚假故事的到底是什么。

As we learn more about how and why false news spreads, we should test interventions to dampen its diffusion. For example, though it was disheartening to learn that humans are more responsible for the spread of false stories than previously thought, this finding also implies that behavioral interventions may succeed in stemming the tide of falsity. It could be, for example, that labeling news stories, in much the same way we label food, could change the way people consume and share it.

在我们更多地了解虚假新闻传播的方式和原因之后,我们应该对一些干预方式进行测试,以遏制虚假新闻的扩散。例如,尽管人类对传播虚假故事的作用比我们之前以为的更大,这令人沮丧,但这个发现也意味着,行为干预也许可以阻挡虚假信息传播的潮流。例如,我们也许可以像给食物贴标签那样给新闻故事贴上标签,从而改变人们消费和分享它的方式。

Financial incentives are another possible tool. The social media advertising market creates incentives for the spread of false stories because their wider diffusion makes them profitable. If platforms were to demote accounts or posts that disseminated false stories, using algorithms to weed out falsehoods, the financial incentives would presumably be reduced. The tricky question, of course, would be: Who gets to decide what is true and false?

财务激励是另一个可能有用的工具。社交媒体广告市场为虚假新闻的传播创造了动机,因为它们传播得越广,就越有利可图。如果平台能够降低那些散布虚假故事的账户或帖子的级别,利用算法清除谎言,那么,财务激励可能会随之减弱。当然,最棘手的问题是:谁来确定哪些故事是真实的,哪些是虚假的?

Our research is just the beginning. A more robust identification of the factors that drive the spread of true and false news will require direct interaction with users through interviews, surveys and lab experiments. We could also benefit from randomized controlled trials of efforts to dampen the spread of false stories.

我们的研究只是个开始。如果想要更准确地找出推动传播真实和虚假新闻的因素,那就需要通过访谈、调查和实验室实验,与用户进行直接互动。我们还可以对抑制虚假故事传播的各种努力进行随机对照的试验,从中取得一些收获。

Some notion of truth is central to the proper functioning of nearly every realm of human endeavor. If we allow the world to be consumed by falsity, we are inviting catastrophe.

了解真相对于人类活动的几乎每一个领域的正常运行都至关重要。如果我们听任这个世界被虚假吞噬,就会招致灾难。

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