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首页> 外文会议>International Computer Conference, Computer Society of Iran >A Novel Method for Detecting Fake news: Deep Learning Based on Propagation Path Concept
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A Novel Method for Detecting Fake news: Deep Learning Based on Propagation Path Concept

机译：一种检测假新闻的新方法：基于传播路径概念的深度学习

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摘要

In the modern world, social media are extensively used for the purpose of communication, business and education. Although ease of use and simple accessibility to social media has expanded their applications, but unfortunately, they are associated with potential dangers which may negatively influence users. As main item, the publication of fake news can negatively affect various aspects of life (political, social, economic, etc.), therefore researchers have studied various methods to address the fake news detection. One way to check and detect fake news is to use the available features in news propagation path, news publisher and users. In this paper, an attempt has been made to investigate fake news detection based on these features and a proposed deep neural network model.
机译：在现代世界中，社交媒体广泛用于沟通，商业和教育的目的。 虽然易用性和对社交媒体的简单可访问性扩展了他们的应用，但不幸的是，它们与可能对用户产生负面影响的潜在危险有关。 作为主要项目，假新闻的出版物可以对生命（政治，社会，经济等）产生负面影响，因此研究人员研究了各种方法来解决假新闻检测。 检查和检测假新闻的一种方法是使用新闻传播路径，新闻发布商和用户中的可用功能。 本文基于这些特征和提出的深神经网络模型，已经尝试调查假新闻检测。

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