Analysis of Articles that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes
Analysis of Articles that Correct Other Posts on Social Media Aimed at Promoting the Experience in Examining Fakes
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DOI：
10.1109/icoco56118.2022.10031731
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
R. Onuma;H. Kaminaga;H. Nakayama;Y. Miyadera;Keito Suzuki;Shoichi Nakamura
中科院分区：
文献类型：
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作者：
R. Onuma;H. Kaminaga;H. Nakayama;Y. Miyadera;Keito Suzuki;Shoichi Nakamura
社交媒体越来越多地被用作收集各种各样信息的工具。然而，社交网络服务上的有用帖子中混杂着虚假文章。用户在使用社交网络服务时判断文章的真假是可取的。然而，这种判断对于没有经验的用户来说是困难的，因为判断文章真实性的技能应该通过经验的积累来获得。在这项研究中，我们的目标是通过根据对文章的他人反应分析来推荐值得注意的文章，开发获取鉴别虚假文章经验的方法。本文描述了根据人们对社交网络服务上文章的反应特征提取纠正其他帖子的文章的方法，以及通过分析此类文章提取虚假文章候选的方法。最后，我们描述了一个使用原型系统的实验，并根据实验结果讨论了我们系统的有效性。
Social media is increasingly being used as a tool to gather a wide variety of information. However, there are fake articles on social networking services mixed in with useful posts. It is desirable for users to use social networking services while determining the truth or falsity of articles. However, such judgement is difficult for inexperienced users since the skills to determine the authenticity of articles should be obtained by a stacking of experiences. In this research, we aim to develop methods for gaining experience with examining fake articles by suggesting noteworthy articles on the basis of an analysis of others’ responses to the articles. This paper describes methods for extracting articles that correct other posts on the basis of the characteristics of people’s responses to articles on social networking services and for extracting candidates for fake articles by analyzing such articles. Finally, we describe an experiment using a prototype system and discuss the effectiveness of our system as based on its results.