Fake news existed ever since there was news, from rumors to printed media then radio and television. Recently, the information age, with its communications and Internet breakthroughs, exacerbated the spread of fake news. Additionally, aside from e-Commerce, the current Internet economy is dependent on advertisements, views and clicks, which prompted many developers to bait the end users to click links or ads. Consequently, the wild spread of fake news through social media networks has impacted real world issues from elections to 5G adoption and the handling of the Covid- 19 pandemic. Efforts to detect and thwart fake news has been there since the advent of fake news, from fact checkers to artificial intelligence-based detectors. Solutions are still evolving as more sophisticated techniques are employed by fake news propagators. In this paper, R code have been used to study and visualize a modern fake news dataset. We use clustering, classification, correlation and various plots to analyze and present the data. The experiments show high efficiency of classifiers in telling apart real from fake news.
翻译：从传闻到印刷媒体,然后是广播和电视,自有新闻以来就出现了假消息。最近,信息时代,由于通信和互联网的突破,加剧了假新闻的传播。此外,除了电子商务之外,当前的互联网经济还依赖于广告、观点和点击,这促使许多开发商诱使终端用户点击链接或广告。因此,通过社交媒体网络的虚假新闻的狂野传播影响了从选举到5G的通过和对Covid-19大流行病的处理等真实世界问题。自假新闻出现以来,发现和挫败假新闻的努力已经出现,从事实检查器到人工智能探测器。随着假新闻传播者使用更先进的技术,解决方案仍在不断演变。在这篇论文中,R码被用于研究和想象现代假新闻数据集。我们使用集群、分类、关联和各种图纸来分析和展示数据。实验显示,分类员在真实地讲述与假新闻分开的情况方面效率很高。
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