Prevalence and Propagation of Fake News

Autor: Banafsheh Behzad, Bhavana Bheem, Daniela Elizondo, Susan Martonosi
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Statistics and Public Policy, Vol 10, Iss 1 (2023)
Druh dokumentu: article
ISSN: 2330443X
2330-443X
DOI: 10.1080/2330443X.2023.2190368
Popis: ABSTRACTIn recent years, scholars have raised concerns on the effects that unreliable news, or “fake news,” has on our political sphere, and our democracy as a whole. For example, the propagation of fake news on social media is widely believed to have influenced the outcome of national elections, including the 2016 U.S. Presidential Election, and the 2020 COVID-19 pandemic. What drives the propagation of fake news on an individual level, and which interventions could effectively reduce the propagation rate? Our model disentangles bias from truthfulness of an article and examines the relationship between these two parameters and a reader’s own beliefs. Using the model, we create policy recommendations for both social media platforms and individual social media users to reduce the spread of untruthful or highly biased news. We recommend that platforms sponsor unbiased truthful news, focus fact-checking efforts on mild to moderately biased news, recommend friend suggestions across the political spectrum, and provide users with reports about the political alignment of their feed. We recommend that individual social media users fact check news that strongly aligns with their political belief and read articles of opposing political bias. Supplementary materials for this article are available online.
Databáze: Directory of Open Access Journals
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