How Fake News Spreads Online: The Math
Models similar to those used to track disease show what happens when too much information hits social media networks
What fuels these stories' astounding popularity? Are we an especially credulous species? Maybe not; perhaps we're just overloaded. Almost anything may go viral, according to a basic model of how news spreads on social media that was published in June in Nature Human Behavior. Due to information overload, some fake news would still spread to thousands (or perhaps millions) of people in a perfect society where everyone wants to disseminate true news and is able to verify the accuracy of every claim. Frequently, it is not even possible to confirm everything that enters one's news stream. "Even if you're skilled at discerning, if you live in a society where you're constantly being inundated with garbage, you're only seeing a fraction of what's out there,
It's likely that in the virtual world, a link, video, phrase, or other piece of online information—which Menczer and his colleagues refer to as a "meme"—will spread because of a picture's aesthetic value or an article's persuasiveness. The researchers show, however, that only three unavoidable elements can account for a network's incapacity to tell whether a meme is true or false, even if an individual can. There is a great quantity of information available, people only have so much time and attention to spend browsing through their news feeds and deciding what to share, and the underlying social network structures. The worst memes are disseminated at the expense of the better ones by the three of them working together.
Agent-based models, which use active engagement from "agents," who are just people, are mathematical frameworks for investigating how memes spread on social media networks. These simulations, which look at how diseases propagate through a society, are where these models' ancestors come from. Imagine a diagram in which each agent is symbolized by a dot, or node, and is connected to other nodes, which stand in for friends or followers, by lines. By shaking hands or sharing a meme with Bob and Clive, respectively, Alice could spread the infection to them if she becomes "infected" with the flu virus or a piece of fake news, for example. In turn, Bob and Clive could spread the disease to their connections,
However, information scientist Kristina Lerman of the University of Southern California, who was not involved in the development of the new model, cautions, "Information is not a virus." While we often only have to deal with one or, at least, a few flu strains at once, the number of memes vying to infect us is astounding. By supposing that each person has a screen on which they can observe incoming memes, the modelers take into account this abundance. The algorithm estimates the likelihood that Alice would produce and distribute a new meme, such as a video of her dancing cockatoo, and it does the same for all potential new memes produced by all other users. Due to the fact that fresh memes increase the overall amount of information in
Another parameter counts how many items Alice watches in her extensive news feed before deciding to share an already-existing meme with her connections rather than coming up with a new one. This parameter acts as a stand-in for the attention span—the details that Alice paid attention to. Once Alice sends a message, it shows up on the screens of Bob, Clive, and other people. These people then decide whether to make their own memes or share one from their feeds.
Content Source:- https://www.scientificamerican.com/article/how-fake-news-goes-viral-mdash-heres-the-math/
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