[YS Learn] The psychology, science, and tech behind fake news, and what makes it harder to crack
Fake news: A term used to describe the dissemination of false information as news, which is seen as damaging to a person or entity.
While the term seems to have emerged around the end of the 19th century, it was shortly before the US Presidential Elections in 2016 that ‘fake news’ started gaining prominence in our society. Now, in the 21st century, the word has become part of our daily lexicon.
The frequency and power of fake news rose when Cambridge Analytica, a British political consulting firm, used Facebook data during the 2016 elections to impact the voting results. In 2020, the flow of pandemic-related misinformation surged and was further fuelled by social media platforms and messaging channels like WhatsApp.
The Netflix documentary — The Social Dilemma — pointed out that fake news on social media platform Twitter travels 6X faster than real news. A Harvard Business Review report adds that people let their guard down on online platforms like Facebook and Twitter, where friends, family members, and coworkers share photos, gossip, and a wide variety of other information.
In the same report, S.Shyam Sundar, Communication Professor, Pennsylvania State University, says, “People are less sceptical of the information they encounter on platforms that are personalised through friend requests, etc.”
A majority of conversations driven on social media platforms are on topics like health, business, personal relationships, politics, religion, and education. Meanwhile, decades of research done by scholars and academicians tells us that it is not uncommon for people to search for and believe in information that conforms to their beliefs.
“The idea of the algorithms of most social media platforms isn’t to provide the right news or information, but it is about giving you the information you want to read. So, that means, you will see what you believe in; if your belief systems are strongly inclined towards one stream of thought, you will see that on your feeds. The idea is to get more people to be online on the platforms,” explains an ethical hacker.
This sentiment also echoes throughout the Netflix documentary - The Social Dilemma, which cites the HBR report, which stresses the need to learn more about platform-based detection and interventions.
Fake is truer than truth
The Science magazine, in a report titled — 'The spread of true and false news online' — worked closely with 16 scientists to understand how fake news and false information spread on social media platforms. It used a data set of rumour cascades on Twitter from 2006 to 2017.
The report states that nearly 126,000 rumours were spread by about three million people. False news, as the report says, reached more people than the truth, while the top one percent of fake news cascades diffused between 1,000 and 100,000 people. In fact, the truth rarely diffused to more than 1,000 people.
“It’s the way the human mind works. We want to believe in something sensational and different. And we see that in news. Even today, everyone has polarised views and opinions, they, therefore, look for something that supports their view,” explains a psychologist in Bengaluru.
He adds that the amount of information that people are bombarded with today makes it difficult for them to stay unbiased.
“The social media platforms want you to build a world where you see what you want to see, read what you want to read, and believe what you want to believe. It is known that it isn’t a person who does this, but the algorithms pick it up and learn based on what is fed to them. It isn’t right or wrong, or false or true,” explains a hacker.
The Science journal explains briefly how the science behind fake news work. It says, “A rumour cascade begins on Twitter when a user makes an assertion about a topic in a tweet, which could include written text, photos, or links to articles online. Others then propagate the rumour by retweeting it. A rumour’s diffusion process can be characterised as having one or more cascades, which we deﬁne as instances of a rumour-spreading pattern that exhibits an unbroken retweet chain with a common, singular origin.”
For example, the report further explains, an individual could start a rumour cascade by tweeting a story or claim with an assertion in it, and another individual could independently start a second rumour cascade on the same story or claim, except both relate to the same story or claim.
If they remain independent, they represent two cascades of the same rumour. The number of cascades that make up a rumour is equal to the number of times the story or claim was independently tweeted by a user, and not retweeted. These cascades can be as small as size one, meaning no one retweeted the original tweet.
But, it isn’t all social media
“Some findings from our research cast doubt on seemingly obvious explanations for why false news travels so quickly and broadly. For example, you might assume that social media heavy hitters are behind the successful spread of false news, but our data revealed the opposite.
"Those who spread false news were significantly less connected than those who spread true news — they had fewer followers, followed fewer people, were less active on Twitter, were “verified” less often, and had been on Twitter a shorter time. All this suggests that falsity diffuses farther and faster despite the differences between the two groups, and not because of them,” the Science journal notes.
The report also points out that people are attracted by novelty, forcing them to share information faster. As per the ‘novelty hypothesis,’ novelty attracts the attention of users and encourages sharing, thereby giving a certain status on those who seem to know more. And, false news is more novel than the truth.
Another HBR report states that modern investment funds use social media sentiment to inform their algorithmic trading practices. When false news infiltrates such media, these automated traders consume and trade on that particular information.
“No one has robustly measured the losses generated by algorithmic trading based on false news, but anecdotal examples suggest that social media’s impact on the economy may be large,” says the report.