Detecting toxic content online and the effect of training data on classification performance

Zhao, Z., Zhang, Z. and Hopfgartner, F. orcid.org/0000-0003-0380-6088 (Submitted: 2019) Detecting toxic content online and the effect of training data on classification performance. EasyChair. (Submitted)

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2019 The Author(s). For re-use permissions please contact the Author(s).
Keywords: classifier performance; Convolutional Neural Network; deep learning; Deep Neural Network; detecting hate speech; hate speech; learning curve; machine learning; multi-label classification; Natural Language Processing; neural network; NLP; offensive language; text classification; text mining; toxic comment; toxic content; toxic content classification; training data
Dates:
  • Submitted: 1 April 2019
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 13 Jul 2020 13:04
Last Modified: 13 Jul 2020 14:05
Published Version: https://easychair.org/publications/preprint/XGmR
Status: Submitted
Identification Number: https://doi.org/10.29007/z5xk

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