Facebook上美国新闻来源用户粘性的时间动态

Alireza Mohammadinodooshan, Niklas Carlsson
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引用次数: 0

摘要

最近,研究人员对新闻的可靠性和政治偏见如何影响Facebook用户的参与度进行了建模,通过使用分享、点赞等互动指标来衡量。然而,Facebook用户对不同程度的偏见和可靠性新闻的参与的时间动态研究较少。鉴于COVID-19大流行,量化大流行如何改变用户对各种新闻的参与也很重要。本文首次对Facebook用户的互动动态进行了时间研究,同时考虑了发布者的偏差和可靠性。我们考虑了992家美国出版商的数据集,研究时间跨度从2018年1月到2022年7月。这使我们能够准确评估新冠疫情对Facebook用户与不同类别新闻互动的时间动态的影响。我们的研究考察了这两个参数对Facebook用户粘性的影响,使用了每个发行商和汇总统计数据。我们的分析揭示了几个发现,包括不同偏见和可靠性类别的出版商在新冠疫情爆发期间和之后经历了显著不同的参与动态水平。例如,我们表明,最不可靠的新闻在covid期间表现出最可观的关注者增长,而最可靠的新闻来源在后covid期间表现出最大的关注者增长率。我们还发现,在新冠肺炎疫情爆发后,用户与Facebook新闻帖子的互动率(互动次数除以关注者数量)甚至比疫情爆发前还要小。此外,我们展示了COVID-19的爆发如何在与几种新闻类型接触的时间动态中造成统计上显着的结构性断裂,并量化了这种影响。随着社交媒体成为危机期间流行的新闻来源,观察到的时间动态为了解近年来信息的消费方式提供了重要见解,使研究人员和公共部门都受益。
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Temporal Dynamics of User Engagement with U.S. News Sources on Facebook
Recently, researchers have modeled how reliability and political bias of news may affect Facebook users' engagement, as measured using interaction metrics such as the number of shares, likes, etc. However, the temporal dynamics of Facebook users' engagement with news of varying degrees of bias and reliability is less studied. In light of the COVID-19 pandemic, it is also important to quantify how the pandemic changed user engagement with various news. This paper presents the first temporal study of Facebook users' interaction dynamics, accounting for both the bias and reliability of the publishers. We consider a dataset of 992 U.S. publishers, and the study spans the period from Jan. 2018 to July 2022. This allows us to accurately assess the effect of the covid outbreak on the temporal dynamics of Facebook users' interactions with different classes of news. Our study examines these two parameters' effect on Facebook user engagement using both per-publisher and aggregated statistics. Several findings are revealed by our analysis, including that publishers in different bias and reliability classes experienced significantly different levels of engagement dynamics during and following the covid outbreak. For example, we show that the least reliable news exhibited the most considerable growth of followers during the covid period and the most reliable news sources exhibited the greatest growth rate of followers during the post-covid period. We also show that the interaction rate (number of interactions normalized over the number of followers) with Facebook news posts during the post-covid period is smaller than it was even before the outbreak. Furthermore, we demonstrate how the COVID-19 outbreak caused statistically significant structural breaks in the temporal dynamics of engagement with several types of news, and quantify this effect. With social media becoming a popular news source during crises, the observed temporal dynamics provide important insights into how information was consumed over the recent years, benefiting both researchers and public sectors.
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