The spread of true and false news online

来自集智百科
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目录

Author

Soroush Vosoughi,1 Deb Roy,1 Sinan Aral2*

Abstract

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.

Data

  • They 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.

Figures

  • depth :the number of retweet hops from the origin tweet overtime, where a hop is a retweet by a new unique user
  • size :the number of users involved in the cascade over time
  • maximum breadth:the maximum number of users involved in the cascade at any depth
  • structural virality:a measure that interpolates between content spread through a single, large broadcast and that which spreads through multiple generations, with any one individual directly responsible for only a fraction of the total spread

根据代码和数据复制的结果:

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