Developing Technology Tools to Combat Fake Science

Chris Impey, Alexander Danehy

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Adults in the United States have a low level of science literacy, and public consensus on major scientific issues like climate change and evolution is hampered by pervasive misinformation and “fake” science on the Internet, often spread by social media. The situation represents a threat to the functioning of civic society. The paper reports on a project to combat scientific misinformation by automatically identifying it using machine learning. Neural networks were trained using sets of non-technical articles selected by science undergraduates on the Internet, with equal numbers of articles containing legitimate science and science misinformation. Climate change and evolution were used as topics for this testbed. After experimenting with various machine learning algorithms, an accuracy above 90% was achieved for the neural net identifying the real science content. In the next phase of the project, this technology will be scaled to large samples of content drawn from CommonCrawl, and it will be applied across more domains of science. Then it will be deployed as a web browser extension that presents the probability that a particular web page has real or fake science, and as a smartphone app for that allows users to classify articles as real or fake.

Original languageEnglish (US)
Title of host publicationAdvances in Information and Communication - Proceedings of the 2022 Future of Information and Communication Conference, FICC
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030980115
StatePublished - 2022
EventFuture of Information and Communication Conference, FICC 2022 - Virtual, Online
Duration: Mar 3 2022Mar 4 2022

Publication series

NameLecture Notes in Networks and Systems
Volume438 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceFuture of Information and Communication Conference, FICC 2022
CityVirtual, Online


  • Machine learning
  • Neural networks
  • Science misinformation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications


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