L.M. Swank, Bsc
Vague news and fake news
During the COVID-19 pandemic, some groups of people engaged in more social distancing than others. It has been shown that at least part of this difference can be attributed to different beliefs about the coronavirus’ severity, which partly originates from media exposure. Aiming to explain the effects of biased information on citizens’ decision making, I develop a theoretical model in which citizens’ beliefs about their optimal personal decisions are based on the media’s reports. The media notices their power on citizens’ beliefs and decisions and slants information. I show that if citizens know that the media outlet is biased, slanting is of no avail and citizens’ decisions are optimal. In contrast, if citizens are uncertain about the outlet’s bias, citizens’ decisions get affected without any additional information. As a reaction, citizens acquire additional information about the outlet’s motives. I test the model’s predictions using data about the COVID-19 outbreak where I measure citizens’ information acquisitions on media outlets as their web searches on ’fake news’. I display positive evidence that the search term ’fake news’ increases in popularity if the average measured emotion in news reports gets more variable. Moreover, in line with the model’s predictions, I show that citizens only react to unexpected emotional changes. In contrast, if citizens expect the emotional variability in news reports, the popularity of the search term ’fake news’ remains the same.
|Last modified:||06 November 2020 1.46 p.m.|