发生了什么事?2016年美国总统大选期间假新闻出版商内容的传播

Ceren Budak
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引用次数: 49

摘要

假新闻出版商制作的内容的传播是2016年美国总统选举中讨论最多的特征之一。然而,人们对这些内容的流行程度和焦点知之甚少,它的流行程度如何随着时间的推移而变化,以及这种流行程度如何与重要的选举动态相关。在本文中,我们使用在日常层面上提到两位总统候选人的推文,这些推文中提到的新闻内容以及来自全国代表性电话采访的开放式回复来解决这些问题。我们的分析结果为新闻消费者和新闻工作者强调了各种重要的教训。我们发现:(i)传统新闻生产者总体上优于假新闻生产者,(ii)假新闻出版商制作的内容的流行度在竞选过程中增加-特别是在提到克林顿的推文中,以及(iii)这种流行度的变化与克林顿的净好感度变化密切相关。谈到内容,我们(iv)识别假新闻媒体和传统新闻媒体在议程设置上的异同,并表明(v)与传统新闻媒体相比,最常被报道阅读、看到或听到的关于候选人的信息与假新闻媒体制作的内容更接近,尤其是共和党选民保留的关于克林顿的信息。我们还将保留信息的虚假程度建模为人口特征的函数。对平台所有者、新闻消费者和记者的影响进行了讨论。
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What happened? The Spread of Fake News Publisher Content During the 2016 U.S. Presidential Election
The spread of content produced by fake news publishers was one of the most discussed characteristics of the 2016 U.S. Presidential Election. Yet, little is known about the prevalence and focus of such content, how its prevalence changed over time, and how this prevalence related to important election dynamics. In this paper, we address these questions using tweets that mention the two presidential candidates sampled at the daily level, the news content mentioned in such tweets, and open-ended responses from nationally representative telephone interviews. The results of our analysis highlight various important lessons for news consumers and journalists. We find that (i.) traditional news producers outperformed fake news producers in aggregate, (ii.) the prevalence of content produced by fake news publishers increased over the course of the campaign-particularly among tweets that mentioned Clinton, and (iii.) changes in such prevalence were closely following changes in net Clinton favorability. Turning to content, we (iv.) identify similarities and differences in agenda setting by fake and traditional news media and show that (v.) information individuals most commonly reported to having read, seen or heard about the candidates was more closely aligned with content produced by fake news outlets than traditional news outlets, in particular for information Republican voters retained about Clinton. We also model fake-ness of retained information as a function of demographics characteristics. Implications for platform owners, news consumers, and journalists are discussed.
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