网络社区中仇恨或攻击性推文的识别

2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA) Pub Date : 2020-11-12 DOI:10.1109/ICETA51985.2020.9379227

K. Machová, D. Suchanic, V. Maslej-Krešňáková

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引用次数: 1

摘要

本文的重点是将文本分类为仇恨言论或攻击性语言，它们代表了网络空间中使学习和交流复杂化的不健康现象。这种分类是通过使用深度神经网络训练模型来实现的。用隐藏层中不同数量的神经元、三种不同的优化器和不同的学习率对网络进行了测试。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Recognition of Hate or Offensive Tweets in the Online Communities

The paper focuses on classification of text into categories as hate speech or offensive language which represent unhealthy phenomena complicating learning and communication in online space. This classification was achieved by training a model using a deep neural network. The network was tested with different amounts of neurons in the hidden layer, with three distinctive optimizers and with various learning rates.

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2020 18th International Conference on Emerging eLearning Technologies and Applications (ICETA)

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