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Information Cascades in Social Media

This article delves into the different instances where information cascades show up in social media. This article drew specifically from research done by a data scientist at Facebook, who found some interesting patterns on the way information is shared and spread. On Facebook, information is shared through the things that friends post and like that may show up on one’s newsfeed. The research showed that the factors that determined how a post would be shared was:

  • network structure, e.g. who initially posted it?
  • temporal patterns, e.g. how quickly it propagated?
  • content?
  • origins?
  • veracity, e.g. was it true or not?

 

One of the biggest things that determined whether a post would become viral was its content. If the post was a meme, or a picture it would tend to gather more views which led the post to become shared more often, which then meant it was visible on more peoples’ newsfeeds. The research concluded that social networks not only spread information to a mass audience, but can also shape the way the information is being taken in by individuals. Factors such as who posted the content, and how many people were “liking” a specific post would determine the information cascade that would result. Studying these various information cascades in social media can predict what types of posts would become viral and reach a wider audience. This could play an important role in things such as political campaigns, and influence the way that certain third parties will structure their information in order to reach the right audience. Overall, this article was very interesting as it showed how many information cascades are present in social media, and how big of a role they play in what people see on their social media.

Article Source: https://civic.mit.edu/blog/erhardt/learning-from-political-experiments-and-information-cascades-on-facebook

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