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美国 Reddit 用户中大型地理分类在网络新闻传播中的作用。

The role of the big geographic sort in online news circulation among U.S. Reddit users.

机构信息

University of Michigan, Ann Arbor, USA.

Bell Labs, Cambridge, UK.

出版信息

Sci Rep. 2023 Apr 25;13(1):6711. doi: 10.1038/s41598-023-33247-3.

DOI:10.1038/s41598-023-33247-3
PMID:37185346
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10126553/
Abstract

Past research has attributed the circulation of online news to two main factors-individual characteristics (e.g., a person's information literacy) and social media effects (e.g., algorithm-mediated information diffusion)-and has overlooked a third one: the critical mass created by the offline self-segregation of Americans into like-minded geographical regions such as states (a phenomenon called 'The Big Sort'). We hypothesized that this latter factor matters for the online spreading of news not least because online interactions, despite having the potential of being global, end up being localized: interaction probability is known to rapidly decay with distance. Upon analysis of more than 8M Reddit comments containing news links spanning four years, from January 2016 to December 2019, we found that Reddit did not work as an 'hype machine' for news (as opposed to what previous work reported for other platforms, circulation was not mainly caused by platform-facilitated network effects). Rather, news circulation in Reddit worked as a supply-and-demand system: news items scaled linearly with the number of users in each state (with a scaling exponent [Formula: see text]  [Formula: see text], and a goodness of fit [Formula: see text]). Furthermore, deviations from such a universal pattern were best explained by state-level personality and cultural factors ([Formula: see text]), rather than socioeconomic conditions ([Formula: see text]) or political characteristics ([Formula: see text]). Higher-than-expected circulation of any type of news was found in states characterised by residents who tend to be less diligent in terms of their personality (low in conscientiousness) and by loose cultures understating the importance of adherence to norms (low in cultural tightness). Interestingly, the combination of those factors with low levels of education was then associated with the circulation of a particular type of news, that is, misinformation. These results suggest that online interactions are geographically bounded and, as such, news circulation cannot be studied purely as an Internet phenomenon but should be grounded into a user's offline cultural environment, which has become increasingly segregated over the decades, and is admittedly hard to change.

摘要

过去的研究将在线新闻的传播归因于两个主要因素——个人特征(例如,一个人的信息素养)和社交媒体的影响(例如,算法介导的信息扩散)——而忽略了第三个因素:美国人离线自我隔离到志同道合的地理区域(如州)所产生的临界质量,这种现象被称为“大分裂”。我们假设,这一因素对于新闻的在线传播很重要,尤其是因为尽管在线互动具有全球性的潜力,但最终还是本地化的:互动概率随着距离的增加而迅速衰减。在对 2016 年 1 月至 2019 年 12 月期间跨越四年的超过 800 万条包含新闻链接的 Reddit 评论进行分析后,我们发现 Reddit 并没有成为新闻的“炒作机器”(与之前其他平台报告的工作相反,传播并不是主要由平台促进的网络效应引起的)。相反,Reddit 上的新闻传播是一个供求系统:新闻内容与每个州的用户数量呈线性相关(具有[公式:见正文]的标度指数[公式:见正文],拟合优度[公式:见正文])。此外,这种普遍模式的偏差可以通过州一级的个性和文化因素([公式:见正文])来最好地解释,而不是社会经济条件([公式:见正文])或政治特征([公式:见正文])。在那些居民个性上更不勤奋(尽责性低)和文化上轻视遵守规范的重要性(文化紧密度低)的州,任何类型的新闻的传播都超过预期。有趣的是,这些因素与低教育水平相结合,然后与特定类型的新闻(即虚假信息)的传播有关。这些结果表明,在线互动具有地理限制,因此,新闻传播不能纯粹作为互联网现象来研究,而应该基于用户的线下文化环境,这种环境在过去几十年中越来越分裂,而且确实很难改变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/b8914aece92b/41598_2023_33247_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/349a2f7c01a1/41598_2023_33247_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/67a9b7132868/41598_2023_33247_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/953e922a7794/41598_2023_33247_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/89f737663721/41598_2023_33247_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/35e6df6cd837/41598_2023_33247_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/b8914aece92b/41598_2023_33247_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/349a2f7c01a1/41598_2023_33247_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/67a9b7132868/41598_2023_33247_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/953e922a7794/41598_2023_33247_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/89f737663721/41598_2023_33247_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/35e6df6cd837/41598_2023_33247_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f332/10130130/b8914aece92b/41598_2023_33247_Fig6_HTML.jpg

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