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.

本文使用 R 代码研究和可视化现代 fake news 数据集，通过聚类、分类、相关性和各种图表分析及呈现数据，并展示了分类器在分辨真假新闻方面的高效性。