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Text-mining-based Fake News Detection Using Ensemble Methods

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Abstract

Social media is a platform to express one’s views and opinions freely and has made communication easier than it was before. This also opens up an opportunity for people to spread fake news intentionally. The ease of access to a variety of news sources on the web also brings the problem of people being exposed to fake news and possibly believing such news. This makes it important for us to detect and flag such content on social media. With the current rate of news generated on social media, it is difficult to differentiate between genuine news and hoaxes without knowing the source of the news. This paper discusses approaches to detection of fake news using only the features of the text of the news, without using any other related metadata. We observe that a combination of stylometric features and text-based word vector representations through ensemble methods can predict fake news with an accuracy of up to 95.49%.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Karnataka, Mangalore, 575025, India

    Harita Reddy, Namratha Raj, Manali Gala & Annappa Basava

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  1. Harita Reddy
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  2. Namratha Raj
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  4. Annappa Basava
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Corresponding author

Correspondence to Harita Reddy.

Additional information

Recommended by Associate Editor Matjaz Gams

Harita Reddy received the B. Tech. degree in computer science and engineering from National Institute of Technology Karnataka, India in 2019. She is currently working as a software engineer at Uber, India.

Her research interests include data mining, machine learning and social network analysis.

Namratha Raj received the B. Tech. degree in computer science and engineering from National Institute of Technology Karnataka, India in 2019.

Her research interests include data science, machine learning, natural language processing and bioinformatics.

Manali Gala received the B. Tech. degree in computer science and engineering from National Institute of Technology Karnataka, India in 2019. She is currently an analyst at Goldman Sachs, India.

Her research interests include machine learning and data analysis.

Annappa Basava received the B. Eng. degree in computer science and engineering from the Govt. B.D.T. College of Engineering, Davangere affiliated to Mysore University, India in 1991, and received the M. Tech. and Ph. D. degrees in computer science and engineering from National Institute of Technology Karnataka, India in 2003 and 2012, respectively. Currently, he is a professor in the Department of Computer Science and Engineering, National Institute of Technology Karnataka, India. He has published more than 100 research papers in international conferences and journals. He has more than 20 years of experience in teaching and research. He was the Organizing Chair of International Conference on Advanced Computing 2013 and he is in the Technical Progam Committee of many international conferences and reviewer of journals. Currently, he is the Chair of India Council of the IEEE Computer Society and he was the Chair of IEEE Mangalore Subsection during 2018. He was the Secretary of IEI Mangaluru Local Centre. He is a Fellow of Institution of Engineers (India) and senior member of IEEE, ACM. Four research scholars completed their Ph. D. under his supervision and 7 scholars are currently enrolled for research under his supervision.

His research interests include cloud computing, big data analytics, distributed computing, software engineering and process mining.

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Reddy, H., Raj, N., Gala, M. et al. Text-mining-based Fake News Detection Using Ensemble Methods. Int. J. Autom. Comput. 17, 210–221 (2020). https://doi.org/10.1007/s11633-019-1216-5

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