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Automatic Detection and Monitoring of Hate Speech in Online Multi-social Media

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Advanced Communication and Intelligent Systems (ICACIS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1749))

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Abstract

Nowadays, we all want to be a part of social media networks in the internet world. Social media has played a critical role in human interaction in the last decade. Every day people use social media huge in numbers and many unfiltered messages are also being posted on multi-social media. Many hate speeches in these messages target an individual or group. In this context, many government and non-government organizations are concerned about these messages and taking some necessary steps to prevent their impact. In this chapter, we have created an intelligent system named “HateDetector-a recursive system” for monitoring and generating alerts on hate speech text for preventive measures on multi-social media with the help of an LSTM-CNN automatic detection model. We have also compared the performance of our LSTM-CNN model with classical machine learning methods in terms of F1 Score, Precision, Recall and, Accuracy.

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Authors and Affiliations

  1. Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

    Ashwini Kumar, Santosh Kumar & Vishu Tyagi

Authors
  1. Ashwini Kumar
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  2. Santosh Kumar
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  3. Vishu Tyagi
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Corresponding author

Correspondence to Ashwini Kumar .

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Editors and Affiliations

  1. Bharath Institute of Higher Education and Research, Chennai, India

    Rabindra Nath Shaw

  2. Systems Research Institute, Warsaw, Poland

    Marcin Paprzycki

  3. The Neotia University, Sarisha, India

    Ankush Ghosh

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Kumar, A., Kumar, S., Tyagi, V. (2023). Automatic Detection and Monitoring of Hate Speech in Online Multi-social Media. In: Shaw, R.N., Paprzycki, M., Ghosh, A. (eds) Advanced Communication and Intelligent Systems. ICACIS 2022. Communications in Computer and Information Science, vol 1749. Springer, Cham. https://doi.org/10.1007/978-3-031-25088-0_53

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  • DOI: https://doi.org/10.1007/978-3-031-25088-0_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-25087-3

  • Online ISBN: 978-3-031-25088-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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