Abstract
The extreme growth and adoption of Social Media and User Generated Content (UGC) websites, in combination with their poor governance and the lack of quality control over the digital content being published and shared, has led information veracity to a continuous deterioration. Therefore, there is a growing need for reliable information assurance, called by both private and public users and authorities. Due to the popularity of the social media and Internet availability all over the world, anyone can provide a piece of information on the web. This may create a ready channel for spreading false, not verified or confusing information, which may be called ‘fake news’. In order to protect the user from online disinformation, some tools have already been proposed. In this article we have described the available online tools and evaluated them using the same dataset, which was created for this study. We have provided the results proving that fake news detection is an increasingly more pressing, yet a difficult research problem.
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Acknowledgement
This work is funded under SocialTruth project, which has received funding from the European Unions Horizon 2020 Research and Innovation Programme under Grant Agreement No. 825477.
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Giełczyk, A., Wawrzyniak, R., Choraś, M. (2019). Evaluation of the Existing Tools for Fake News Detection. In: Saeed, K., Chaki, R., Janev, V. (eds) Computer Information Systems and Industrial Management. CISIM 2019. Lecture Notes in Computer Science(), vol 11703. Springer, Cham. https://doi.org/10.1007/978-3-030-28957-7_13
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DOI: https://doi.org/10.1007/978-3-030-28957-7_13
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