Fake news on social media is better recognised when readers can indicate that the information is incorrect, a recent study of sociologist Jonas Stein shows. According to Stein, the use of a public rating system is therefore a promising weapon in the fight against misinformation, although it does matter by whom the ratings are given.
How can you counter misinformation on social media? This question is at the heart of the doctoral thesis of sociologist Jonas Stein. In a recently published article, he investigated whether misinformation is better recognised if it is accompanied by other people's ratings. Similar public rating systems have already been successfully used for online products or restaurants, for example.
Stein and his colleagues had 4,000 US subjects rate information as 'true' or 'false'. For example, they indicated whether it is true that man-made CO2 emissions increase the risk of wildfires (true). Some of the subjects, before rating the statements themselves, could see what their predecessors had answered. Subjects who could see these ratings were found to be better at recognising fake news than those who did not have access to this information.
But, the study found, it does matter who gave the ratings. Ratings based on the judgements of a diverse group were found to be more accurate than those of a homogeneous group. Stein: 'We saw that when all the reviewers have the same political views this can lead to inaccurate ratings. In turn, these inaccurate ratings cause others to believe that the fake news is true. So in such a case, a rating system actually backfires and makes people less critical'.
Based on his research, Stein concludes that ratings may be an efficient way to counter fake news on platforms where people interact a lot with others who have different views than them. 'We were happy to see that on those platforms ratings make it easier for people to recognise inaccurate information, because this method is faster and cheaper than, say, having a professional fact-check the information'. For platforms where there is less diversity, there is still work to be done before a rating system can be deployed. 'Such platforms need to work on reducing segregation first'.
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