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Machine Learning to Identify Fake News for COVID-19.

Marianna Isaakidou1, Emmanouil Zoulias2, Marianna Diomidous1

  • 1Faculty of Nursing, National and Kapodistrian University of Athens, Athens, Greece.

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International organizations are concerned about fake news. This study introduces an Artificial Intelligence approach, the Decision Trees algorithm, to identify COVID-19 misinformation and disinformation.

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Area of Science:

  • Computer Science
  • Information Science

Background:

  • Fake news, encompassing misinformation and disinformation, is a significant global concern.
  • UNESCO has defined misinformation and disinformation as key aspects of fake news.
  • A European Commission survey revealed that 40% of citizens encounter fake news daily, with 85% recognizing it as a problem.

Purpose of the Study:

  • To introduce an Artificial Intelligence (AI) approach for identifying fake news.
  • To specifically apply the Decision Trees algorithm to detect fake news related to COVID-19.

Main Methods:

  • Utilizing the Decision Trees algorithm, a machine learning technique.
  • Applying the algorithm to a dataset focused on COVID-19 information.

Main Results:

  • The study demonstrates the potential of AI, specifically Decision Trees, in tackling fake news.
  • The approach offers a method for distinguishing authentic information from misinformation/disinformation.

Conclusions:

  • Artificial Intelligence presents a viable solution for combating the spread of fake news.
  • The Decision Trees algorithm can be effectively employed to identify fake news within the context of public health crises like COVID-19.