Massachusetts Institute of Technology (MIT), the Media Lab, E14-526, 75 Amherst Street, Cambridge, MA 02142, USA.
MIT, E62-364, 100 Main Street, Cambridge, MA 02142, USA.
Science. 2018 Mar 9;359(6380):1146-1151. doi: 10.1126/science.aap9559.
We investigated the differential diffusion of all of the verified true and false news stories distributed on Twitter from 2006 to 2017. The data comprise ~126,000 stories tweeted by ~3 million people more than 4.5 million times. We classified news as true or false using information from six independent fact-checking organizations that exhibited 95 to 98% agreement on the classifications. Falsehood diffused significantly farther, faster, deeper, and more broadly than the truth in all categories of information, and the effects were more pronounced for false political news than for false news about terrorism, natural disasters, science, urban legends, or financial information. We found that false news was more novel than true news, which suggests that people were more likely to share novel information. Whereas false stories inspired fear, disgust, and surprise in replies, true stories inspired anticipation, sadness, joy, and trust. Contrary to conventional wisdom, robots accelerated the spread of true and false news at the same rate, implying that false news spreads more than the truth because humans, not robots, are more likely to spread it.
我们研究了 2006 年至 2017 年在 Twitter 上发布的所有已核实的真假新闻故事的差异扩散。这些数据包括由超过 300 万人在 450 多万次推文中分享的约 126000 个故事。我们使用来自六个独立事实核查机构的信息将新闻分类为真实或虚假，这些机构在分类上的一致性达到 95%至 98%。在所有信息类别中，虚假信息的传播范围都明显大于真实信息，而且虚假政治新闻的传播效果比恐怖主义、自然灾害、科学、都市传说或金融信息的传播效果更为显著。我们发现，虚假新闻比真实新闻更新颖，这表明人们更有可能分享新颖的信息。而虚假故事在回复中引发了恐惧、厌恶和惊讶，真实故事则引发了期待、悲伤、喜悦和信任。与传统观点相反，机器人以相同的速度加速了真假新闻的传播，这意味着虚假新闻的传播速度超过了真实新闻，因为传播虚假新闻的不是机器人，而是人类。
