Prevalence and Propagation of Fake News

被引:0
|
作者
Behzad, Banafsheh [1 ]
Bheem, Bhavana [2 ]
Elizondo, Daniela [3 ]
Martonosi, Susan [2 ]
机构
[1] Calif State Univ Long Beach, Informat Syst Dept, Long Beach, CA 90840 USA
[2] Harvey Mudd Coll, Math Dept, Claremont, CA USA
[3] Rutgers State Univ, Math Dept, Piscataway, NJ USA
来源
STATISTICS AND PUBLIC POLICY | 2023年 / 10卷 / 01期
基金
美国国家科学基金会;
关键词
Bias; Policy recommendation; Social media analysis; Truthfulness; MEDIA; ACCOUNTS; TWITTER;
D O I
10.1080/2330443X.2023.2190368
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
In 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. for this article are available online.
引用
收藏
页数:13
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