论文标题
词汇一代检测假新闻
Lexicon generation for detecting fake news
论文作者
论文摘要
随着媒体的数字化，包括主流媒体媒体和社交网络在内的在线资源生成了大量新闻数据。但是，生产和分销的便利性导致了假新闻的发行以及可信的真实新闻。假新闻的普遍传播对个人和社会产生了极大的负面影响。因此，作为一个跨学科研究领域，假新闻检测已成为一个新兴的话题，它吸引了许多研究学科，包括社会科学和语言学。在这项研究中，我们提出了一种主要基于词典的方法，其中包括一个评分系统，以促进土耳其假新闻的检测。我们通过收集一本小说，大规模和可靠的土耳其新闻数据集，并通过为土耳其语构建第一个假新闻探测词典来为文学做出贡献。
With the digitization of media, an immense amount of news data has been generated by online sources, including mainstream media outlets as well as social networks. However, the ease of production and distribution resulted in circulation of fake news as well as credible, authentic news. The pervasive dissemination of fake news has extreme negative impacts on individuals and society. Therefore, fake news detection has recently become an emerging topic as an interdisciplinary research field that is attracting significant attention from many research disciplines, including social sciences and linguistics. In this study, we propose a method primarily based on lexicons including a scoring system to facilitate the detection of the fake news in Turkish. We contribute to the literature by collecting a novel, large scale, and credible dataset of Turkish news, and by constructing the first fake news detection lexicon for Turkish.
