The “novelty hypothesis” explains how — and why — people fall for fake news bots

Social bots, meaning software-controlled social media profiles, are a big part of how fake news spreads and the way they are used to spread lies online is both disturbing and fascinating, but if we only focus on the role of bots, we minimize the role of humans in spreading misinformation.

In 2018 my friend and colleague Filippo Menczer at Indiana University, along with his colleagues Chengcheng Shao, Giovanni Ciampaglia, Onur Varol, Kai-Cheng Yang, and Alessandro Flammini, published the largest-ever study on how social bots spread fake news. They analyzed 14 million tweets spreading 400,000 articles on Twitter in 2016 and 2017. Their work corroborated our finding that fake news was more viral than real news. They also found that bots played a big role in spreading content from low-credibility sources. But the way bots worked to amplify fake news was surprising, and it highlights the sophistication with which they are programmed to prey on the Hype Machine, the ever-expanding universe of websites, social media, text messages, and digital marketing that connects us to one another.

First, bots pounce on fake news in the first few seconds after it’s published, and they retweet it broadly. That’s how they’re designed. And the initial spreaders of a fake news article are much more likely to be bots than humans.

What happens next validates the effectiveness of this strategy, because humans do most of the retweeting. The early tweeting activity by bots triggers a disproportionate amount of human engagement, creating cascades of fake news triggered by bots but propagated by humans through the Hype Machine’s network.

Second, bots mention influential humans incessantly. If they can get an influential human to retweet fake news, it simultaneously amplifies and legitimizes it. Menczer and his colleagues point to an example in their data in which a single bot mentioned @realDonaldTrump (the president’s Twitter handle) nineteen times, linking to the false news claim that millions of votes were cast by illegal immigrants in the 2016 presidential election. The strategy works when influential people are fooled into sharing the content. Donald Trump, for example, has on a number of occasions shared content from known bots, legitimizing their content and spreading their misinformation widely in the Twitter network. It was Trump who adopted the false claim that millions of illegal immigrants voted in the 2016 presidential election as an official talking point.

But bots can’t spread fake news without people. In our ten-year study with Twitter, we found that it was humans, more than bots, that helped make false rumors spread faster and more broadly than the truth. In their study from 2016 to 2017, Menczer and his colleagues also found that humans, not bots, were the most critical spreaders of fake news in the Twitter network. In the end, humans and machines play symbiotic roles in the spread of falsity: bots manipulate humans to share fake news, and humans spread it on through the Hype Machine.

Misleading humans is the ultimate goal of any misinformation campaign. It’s humans who vote, protest, boycott products, and decide whether to vaccinate their kids. These deeply human decisions are the very object of fake news manipulation. Bots are just a vehicle to achieve an end. But if humans are the objects of fake news campaigns, and if they are so critical to their spread, why are we so attracted to fake news? And why do we share it?

One explanation is what Soroush Vosoughi, Deb Roy, and I called the novelty hypothesis. Novelty attracts human attention because it is surprising and emotionally arousing. It updates our understanding of the world. It encourages sharing because it confers social status on the sharer, who is seen as someone who is “in the know” or who has access to “inside information.” Knowing that, we tested whether false news was more novel than the truth in the ten years of Twitter data we studied. We also examined whether Twitter users were more likely to retweet information that seemed to be more novel.

To assess novelty, we looked at users who shared true and false rumors and compared the content of rumor tweets to the content of all the tweets the users were exposed to in the sixty days prior to their decision to retweet a rumor. Our findings were consistent across multiple measures of novelty: false news was indeed more novel than the truth, and people were more likely to share novel information. This makes sense in the context of the “attention economy”. In the context of competing social media memes, novelty attracts our scarce attention and motivates our consumption and sharing behaviors online.

Although false rumors were more novel than true rumors in our study, users may not have perceived them as such. So to further test our novelty hypothesis, we assessed users’ perceptions of true and false rumors by comparing the emotions they expressed in their replies to these rumors. We found that false rumors inspired more surprise and disgust, corroborating the novelty hypothesis, while the truth inspired more sadness, anticipation, joy, and trust. These emotions shed light on what inspires people to share false news beyond its novelty. To understand the mechanisms underlying the spread of fake news, we have to also consider humans’ susceptibility to it.

The post The “novelty hypothesis” explains how — and why — people fall for fake news bots appeared first on Salon.


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