This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: It doesn't take a scientist to figure out that social media can trend toward the negative. But it might take one to figure out why.
In a new paper in PNAS, professor of psychology Joshua Conrad Jackson and colleagues show that algorithms aren't the only driver of online negativity. Another culprit is what psychologists call differentiation, the innate drive to stand out from one's peers. "Negative information is just much more diverse than positive information," Jackson said.
For example, he added, "If you're talking about 'The Odyssey,' this new Christopher Nolan film, the top comment in a thread might be 'I liked it'—but then what else is there to say? If you want to stand out and say something new, you have to talk about something you disliked about the film." Jackson and his colleagues analyzed more than 2 billion comments from 2,150 Reddit communities and found that both threads and communities became more negative over time, and that semantic differentiation drove that trend—that is, negative comments were more semantically unique from what had already been said. They then replicated their observational findings with an experiment that showed that social media users who were primed to be unique posted more negative comments than users who were primed to conform.
We talked to Jackson about takeaways from the paper and potential implications for other forms of media. The interview has been edited for clarity and length. Jackson: We started our paper with Godwin's Law, which is the idea that the longer a conversation continues on social media, the probability of someone being compared to Hitler or Nazis approaches one.
Harvard economists actually tested Godwin's Law, and found that it's not true. But I don't think it was meant to be literally true: I think it was meant to capture this intuition that dialogue on social media is more negative than it needs to be. Of course, feed-ranking algorithms are a big part of the story: These are the algorithms that pick up on divisive content that gets people's attention, keeps people engaged, and makes them angry so that they post their own divisive content, creating a vicious cycle and generating ad revenue in the process.
This paper was kind of a side quest. We wanted to know if conversations would turn negative even in the absence of those algorithms. We found that the entire website of Reddit has become more negative over time.
Extract — continue reading at the source.
