False News Stories Are 70% More Likely To Be Retweeted On Twitter Than True Ones
https://www.marketwatch.com/story/fake-news-spreads-more-quickly-on-twitter-than-real-news-2018-03-08?mod=newsviewer_click
In this MarketWatch article, Kari Paul reports that a recent study conducted by the Massachusetts Institute of Technology on the spreading of false information concluded that “false news stories are 70% more likely to be retweeted than true stories.” The study also stated that false stories “are also retweeted more widely than true statements at every depth of a ‘cascade,'” which is what unbroken tweet chains were referred to as in the study. Surprisingly, when the research team tested the influence of bots in the spreading of fake news by removing them from their dataset, they discovered that the rate of users spreading fake news when compared to true stories was unaffected. While Twitter and other companies have been attempting to figure out ways to combat fake news, the researchers believe that the problem is more complicated than expected, especially since they found that there are many users who unwittingly share the false information in addition to those who share it on purpose.
In relation to CS 2850, this article is a reflection on Chapter 16’s Information Cascades. Information cascades, or herdings, refer to cases where people connected to a network are influenced by each other’s behaviors and decisions, with the end result being a collective outcome despite the existence of alternative choices. In the article’s case, Twitter users are collectively choosing to retweet and spread fake news sources even though alternative sources that contain true information are also present. Professor Sinan Aral, a co-author of the study, explained that users are more attracted to interesting stories, even if they are false, and fake news stories tend to have more exciting details when compared to the facts of real news stories. This attention hook causes users to retweet the source in high numbers, and this large amount of retweets would further persuade even more users to give it retweets since, as Aral notes, it allows them to feel that they are caught up in the public knowledge. This direct-benefit effect of having “a false sense of expertise” might be the root of the fake news problem, as people are rationally concluding that spreading popular posts would make them appear worthy in the network, even if the posts are factually wrong.