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How Graphs Can Model Social Media’s Reach

In the article (, Peter Suderman talks about the concept of regulating social media, and the impact social media has on our everyday lives. Few technological giants, such as Facebook, Twitter and Google have a huge impact on the information people receive. The government argues that this information needs to be treated as a public utility, and that the internet is now the news channel or newspaper of the modern day. However, Suderman argues that regulation comes at a price: more government overreach.

This opinion piece brings up many key issues on the role social media plays in society. One major concept can be modeled by a node edge graph, with each node representing either a social media source or a person. Using this model, we can see that these technological giants have the ability to influence extreme amounts of people from one point. All it takes is Facebook or Twitter promoting a certain article for it to reach millions more people than it previously could have been able to, resulting in a clear push towards that articles agenda. It is hard to argue that technological giants will act without bias, giving credence to the notion that regulation is an ideal solution to the unequal distribution of information.

Additionally, with the way people share social media, we start seeing people being trapped in triangles of circular thought. To explain this, we can once again go back to the node edge graph, where we see person A sharing an article or post. This post will be shared to all their friends. Now suppose two unrelated friends of person A, call them B and C, comment on this post. This now spreads this post to all of their friends, and forms a strong link for all 3 of these people. We can see how these triangles will start to form when using social media as a news platform. This creates a bubble of circular thought with these nodes, and eventually isolates them from opposing ideologies.

The crux of Suderman’s argument was the rise of isolation from the real world is a growing issue; this can be shown by the node edge graphs as explained above. Therefore it becomes increasingly important for people to realize how easily information can be biased by technological giants and how easily people can get trapped in bubbles.


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September 2018