首页> 外文会议>International Conference on Intelligent Networking and Collaborative Systems >A Machine Learning Approach to Fake News Detection Using Knowledge Verification and Natural Language Processing
【24h】

A Machine Learning Approach to Fake News Detection Using Knowledge Verification and Natural Language Processing

机译:使用知识验证和自然语言处理的假新闻检测机器学习方法

获取原文

摘要

The term "fake news" gained international popularity as a result of the 2016 US presidential election campaign. It is related to the practice of spreading false and/or misleading information in order to influence popular opinion. This practice is known as disinformation. It is one of the main weapons used in information warfare, which is listed as an emerging cybersecurity threat. In this paper, we explore "fake news" as a disinformation tool. We survey previous efforts in defining and automating the detection process of "fake news". We establish a new fluid definition of "fake news" in terms of relative bias and factual accuracy. We devise a novel framework for fake news detection, based on our proposed definition and using a machine learning model.
机译:由于2016年美国总统选举活动,“假新闻”一词获得了国际人气。它与传播虚假和/或误导性信息的做法有关,以影响流行意见。这种做法被称为缺点。它是信息战中使用的主要武器之一,被列为新兴的网络安全威胁。在本文中,我们探讨了“假新闻”作为一个不诚实工具。我们调查了以往的努力定义和自动化“假新闻”的检测过程。我们在相对偏见和事实准确性方面建立了“假新闻”的新流体定义。我们根据我们建议的定义和使用机器学习模型,设计了一个新颖的假新闻检测框架。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号