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Mind Your Tweet: Abusive Tweet Detection

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Speech and Computer (SPECOM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12997))

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Abstract

The abusive posts detection problem is more complicated than it seems due to its unseemly, unstructured noisy data and unpredictable context. The learning performance of the neural networks attracts researchers to get the highest performing output. Still, there are some limitations for noisy data while training for a neural network. In our work, we have proposed an approach that considers the assets of both the machine learning and neural network to get the most optimum result. Our approach performs with the F1 score of 92.79.

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Notes

  1. 1.

    https://en.oxforddictionaries.com/definition/abusive.

  2. 2.

    https://www.courts.ca.gov/1258.html.

  3. 3.

    https://blog.twitter.com/engineering/en_us/a/2013/new-tweets-per-second-record-and-how.htm.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology (BHU) Varanasi, Varanasi, 221005, India

    Paras Tiwari

  2. Department of Computer Science and Engineering, Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 482005, India

    Sawan Rai

Authors
  1. Paras Tiwari
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  2. Sawan Rai
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Correspondence to Paras Tiwari .

Editor information

Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  2. Moscow State Linguistic University, Moscow, Russia

    Rodmonga Potapova

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Tiwari, P., Rai, S. (2021). Mind Your Tweet: Abusive Tweet Detection. In: Karpov, A., Potapova, R. (eds) Speech and Computer. SPECOM 2021. Lecture Notes in Computer Science(), vol 12997. Springer, Cham. https://doi.org/10.1007/978-3-030-87802-3_63

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  • DOI: https://doi.org/10.1007/978-3-030-87802-3_63

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87801-6

  • Online ISBN: 978-3-030-87802-3

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