真相与传说:了解韩国的在线假新闻网络

B. Sheehy, Sujin Choi, Md. Irfanuzzaman Khan, Bruce Baer Arnold, Yoonmo Sang, Jae-Jin Lee
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摘要

本研究探讨了假新闻网络的特点及其在 2020 年韩国大选期间的传播方式。利用行为者网络理论(ANT),我们评估了网络的核心参与者以及他们之间的联系。结果揭示了负责假新闻传播的视频剪辑和渠道网络的特点。通过对视频网络的分析,我们发现了大量被检测到的假新闻视频以及用户之间的高密度连接。对真实和虚假新闻网络上的新闻视频进行评估后发现,真实新闻网络更为集中。不过,网络的规模可能是造成这些差异的原因之一。对网络集中度的统计显示,用户分散在整个网络中,这说明了网络的分散性。仔细观察视频和频道内部的真实和虚假新闻网络,也会发现类似的趋势。我们发现,真实新闻视频网络的密度高于虚假新闻网络,而虚假新闻频道网络的密度则高于真实新闻频道,这可能表明它们在传播过程中具有更高的活跃度和互联性。我们还发现,假新闻视频短片比真新闻视频短片获得更多的赞,而真新闻视频短片比假新闻视频短片获得更多的不赞。这些发现有力地表明,当人们在 YouTube 上观看假新闻视频时,会更容易接受这些视频。此外,我们还利用语义网络和自动内容分析发现了假新闻中的共同语言模式,这有助于我们更好地了解假新闻传播网络的结构和动态。本文所报告的研究结果为我们了解 2020 年韩国大选期间假新闻如何通过社交网络传播提供了重要启示。本研究的结果对打击假新闻和确保真实报道具有重要意义。
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Truths and Tales: Understanding Online Fake News Networks in South Korea
This study investigates the features of fake news networks and how they spread during the 2020 South Korean election. Using actor–network theory (ANT), we assessed the network’s central players and how they are connected. Results reveal the characteristics of the videoclips and channel networks responsible for the propagation of fake news. Analysis of the videoclip network reveals a high number of detected fake news videos and a high density of connections among users. Assessment of news videoclips on both actual and fake news networks reveals that the real news network is more concentrated. However, the scale of the network may play a role in these variations. Statistics for network centralization reveal that users are spread out over the network, pointing to its decentralized character. A closer look at the real and fake news networks inside videos and channels reveals similar trends. We find that the density of the real news videoclip network is higher than that of the fake news network, whereas the fake news channel networks are denser than their real news counterparts, which may indicate greater activity and interconnectedness in their transmission. We also found that fake news videoclips had more likes than real news videoclips, whereas real news videoclips had more dislikes than fake news videoclips. These findings strongly suggest that fake news videoclips are more accepted when people watch them on YouTube. In addition, we used semantic networks and automated content analysis to uncover common language patterns in fake news, which helps us better understand the structure and dynamics of the networks involved in the dissemination of fake news. The findings reported here provide important insights on how fake news spread via social networks during the South Korean election of 2020. The results of this study have important implications for the campaign against fake news and ensuring factual coverage.
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