In their article, Allcott and Gentzkow (2017) present a theoretical and empirical framework for examining the economics of fake news, focusing on its role in the context of social media during the 2016 United States of America (US) presidential election. It discusses fake news and voting behavior in the presidential election by investigating various aspects of fake news during the election period, including who generates and believes in fake news, the economic model of fake news, and the factors influencing individuals’ capacity to differentiate between authentic and fabricated news.
Additionally, the study examines the polarization of beliefs concerning fake news and identifies the factors associated with ideologically aligned interpretations. It develops research questions aligned with its objectives, including who generates and believes in fake news, how is fake news distinct from biased or tilted media, how to comprehend the economic model of fake news, how much fake news the typical voter sees in the run-up to the 2016 election, and what individual characteristics predict correct beliefs regarding headlines.
Theoretically, social media platforms may be especially conducive to fake news for several reasons (Allcott & Gentzkow, 2017). Firstly, there is almost no entry cost to access social media. The fixed costs of entering the social media market and creating content are extremely small, implying an increase in the relative profitability of the small-scale, short-term strategies fake news producers often employ and a decline in the relative significance of establishing a long-term reputation for quality. Secondly, the display format of social media can make it difficult to verdict the accuracy of an article.
The study employs a combination of research methods, encompassing primary data using survey research and secondary data from various related website scraping, presented in terms of descriptive statistics and linear regression to address research questions. The analysis scope focuses on fake news articles with political implications for the 2016 US presidential elections. The primary data from an online survey conducted post-election through the SurveyMonkey platform is employed to gather information about individuals’ exposure to fake news, their political beliefs, as well as their demographic characteristics, political affiliations, consumption of election-related news, and their recollection and belief in news headlines.
The online sample is reweighted to ensure it aligns with the characteristics of the nationwide adult population. The secondary data of fake news stories are collected from relevant websites, including Snopes, PolitiFact, and BuzzSumo, to build a database of fake news articles. The findings of the analysis are presented using descriptive statistics and a narrative explanation. Additionally, linear regression analysis examines the inference about true versus false news headlines and the associated determinants.
The main findings of the study suggest that while social media referrals play a minor role in driving traffic to mainstream news websites, it has a significantly larger role for fake news websites, and indicate that trust in information obtained through social media is lower when compared to trust in traditional news sources. Additionally, the research confirms that fake news was extensively disseminated and predominantly favored Donald Trump. Furthermore, the typical US adult likely encountered one or more news stories in the months leading up to the election, with a notable emphasis on pro-Trump articles. The study also underscores the positive relationships between education, age, total media consumption, and the accuracy of beliefs regarding the veracity of headlines. Moreover, individuals were more inclined to share fake news if it confirmed their pre-existing beliefs and if they were actively engaged in politics.
While the article provides rigorous analysis and the acknowledgment of its limitations that can be valuable in developing future research on the same subject, it could be advantageous to explicitly incorporate the concept of confirmation bias in decision-making heuristics and biases within the analysis to make it more comprehensive. Confirmation bias represents the inherent tendency to notice, concentrate on, and attribute greater credibility to evidence that aligns with individuals’ pre-existing beliefs.
The propensity of individuals to seek out information that confirms their convictions while disregarding contradictory information is indirectly corroborated by the article’s finding that those with segregated social networks are notably more inclined to trust ideologically aligned articles. This implies that they are less likely to encounter information from their social peer that challenges their existing views. Overall, the article could be a good reminder to carefully filter every information received particularly through social media.
Reference
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of economic perspectives, 31(2), 211-236.
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