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The duration of fake news in online platforms has become a pressing concern, posing significant threats to public trust, democratic method, and societal stability. Addressing this issue requires effective detection methods capable of swiftly identifying and curbing the dissemination of misinformation. However, conventional approaches often rely on content similarity metrics, making them susceptible to manipulation. The review begins by examining the characteristics and motivations behind the creation and dissemination of fake news. It delves into the psychological factors that contribute to the susceptibility of individuals to false information and explores the role of social networks in amplifying its spread. In addition, the paper explores the technological developments on automated detecting methods that include machine learning algorithms and natural language processing that have been utilized to detect fake news content and patterns of its spread. In addition, the review also outlines the intrinsic issues and drawbacks that face the present detection approaches. With the growing importance of fake news dissemination in the online environment, the current paper conducts a comprehensive review of the current research efforts in the sphere of explaining and combating the fake news development. Basing its considerations on a multiplicity of fields such as computer science, communication studies, sociology, and psychology, this review offers a diversified view of the complexity surrounding the online misinformation spread mechanisms. Starting with a profound exploration of the various motives that drive the creation and spread of fake news, this review will not only cover the socio-political and economical ones but also the cognitive biases and psychological reasons that make people so prone to misleading information. Furthermore, it looks at the virality of false narratives, explained through the structural dynamics of social networks and how the architecture of digital platforms can enhance the spread of false information. Drawing upon insights from an array of disciplines including computer science, communication studies, sociology, and psychology, this review presents a multifaceted analysis of the intricate mechanisms driving the dissemination of online misinformation.

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Identifying Fake News Dissemination over the Internet via Cyber Security and Machine Learning

  • 会议论文

  • 发表日期：

    2026年

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  • Neha Tyagi,
  • Harsh Verma,
  • Jai Pruthi,
  • Harpreet Vohra,
  • Durga Rao Manchikanti,
  • Shobha Tyagi

摘要

The duration of fake news in online platforms has become a pressing concern, posing significant threats to public trust, democratic method, and societal stability. Addressing this issue requires effective detection methods capable of swiftly identifying and curbing the dissemination of misinformation. However, conventional approaches often rely on content similarity metrics, making them susceptible to manipulation. The review begins by examining the characteristics and motivations behind the creation and dissemination of fake news. It delves into the psychological factors that contribute to the susceptibility of individuals to false information and explores the role of social networks in amplifying its spread. In addition, the paper explores the technological developments on automated detecting methods that include machine learning algorithms and natural language processing that have been utilized to detect fake news content and patterns of its spread. In addition, the review also outlines the intrinsic issues and drawbacks that face the present detection approaches. With the growing importance of fake news dissemination in the online environment, the current paper conducts a comprehensive review of the current research efforts in the sphere of explaining and combating the fake news development. Basing its considerations on a multiplicity of fields such as computer science, communication studies, sociology, and psychology, this review offers a diversified view of the complexity surrounding the online misinformation spread mechanisms. Starting with a profound exploration of the various motives that drive the creation and spread of fake news, this review will not only cover the socio-political and economical ones but also the cognitive biases and psychological reasons that make people so prone to misleading information. Furthermore, it looks at the virality of false narratives, explained through the structural dynamics of social networks and how the architecture of digital platforms can enhance the spread of false information. Drawing upon insights from an array of disciplines including computer science, communication studies, sociology, and psychology, this review presents a multifaceted analysis of the intricate mechanisms driving the dissemination of online misinformation.