Analysis of the KNN Classifier Distance Metrics for Bulgarian Fake News Detection

Tsvetelina Mladenova, Irena Valova
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引用次数: 12

Abstract

The problem with fake news and click-bait headlines is not new. Despite that this kind of news has existed for many years now, it was just a few years ago that the focus of the scientific community turned to them. Even though there is quite a lot of research on the topic of detecting fake news in general, there is a limited number of studies on fake news in Cyrillic. This paper focuses on the classification of fake news and click-bait headlines from Bulgarian Facebook Pages. The KNN machine-learning algorithm is chosen and four different distance metrics are tested and analyzed.
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保加利亚假新闻检测的KNN分类器距离度量分析
假新闻和点击诱饵标题的问题并不新鲜。尽管这类新闻已经存在了很多年,但直到几年前,科学界的焦点才转向它们。尽管在一般情况下,对假新闻检测的研究相当多,但对西里尔文假新闻的研究数量有限。本文着重于保加利亚Facebook页面的假新闻和点击诱饵标题的分类。选择了KNN机器学习算法,并对四种不同的距离度量进行了测试和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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