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On Twitter, false news travels faster than true stories, study finds

On Twitter, false news travels faster than true stories, study finds

We’ve studied how information is spread throughout networks, and the effects of these internet cascades. In recognizing that information spreads quickly, is has become important to be able to differentiate between the real and fake news that spreads rapidly through social media sites like Twitter.

MIT conducted research that showed the power of fake news–false stories are 70% more likely to be retweet than true stories, a statistic that is frightening. When going on twitter, there is no mechanism to determine which tweets are spreading good or false information throughout the social media website’s network. Researchers argue that the cause of the spread of false information is a result of the novelty of fake news stories. Since these stories tend to have more compelling and interesting details/headings, individuals are more likely to retweet them to followers. To remove all external influences, researchers gathered information on retweets without the presence of bots, and found that the numbers were the same. These findings highlight the need for indicators on social media websites to claim which news stories are credible/not credible in order to reduce to spread of false stories. For big media events, rumors are always created, but stopping this rumors earlier on would benefit society as a whole.

In class, we learned about the importance of early adopters and their influence on the individuals in their immediate network. We can apply this idea of how information is spread through networks to the spread of false news stories on twitter. When a user sees that a certain fraction of his/her friends have retweeted the news story, they too will repost the news story and believe in the information being spread. The point at which the number of followers who repost the news story influence the individual user is known as the tipping point — the point at which is known as the point when there are enough neighbors who have been influenced in a network to influence a neighbor with a different belief. This accurately describes how false information as spread, since as the number of retweets of the fake news story occur, the increased likelihood of a user to retweet it as well.

If social networking sites were able to flag stories that may not be credible, the spread of false information could be reduced.

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