LITHUANIAN HATE SPEECH CLASSIFICATION USING DEEP LEARNING METHODS

The ever-increasing amount of online content and the opportunity for everyone to express their opinions online leads to frequent encounters with social problems: bullying, insults, and hate speech. Some online portals are taking steps to stop this, such as no longer allowing user-generated comments...

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Bibliographic Details
Main Authors: Eglė Kankevičiūtė, Milita Songailaitė, Bohdan Zhyhun, Justina Mandravickaitė
Format: Article
Language:English
Published: Odessa National Academy of Food Technologies 2023-09-01
Series:Автоматизация технологических и бизнес-процессов
Subjects:
Online Access:https://journals.ontu.edu.ua/index.php/atbp/article/view/2621
Description
Summary:The ever-increasing amount of online content and the opportunity for everyone to express their opinions online leads to frequent encounters with social problems: bullying, insults, and hate speech. Some online portals are taking steps to stop this, such as no longer allowing user-generated comments to be made anonymously, removing the possibility to comment under the articles, and some portals employ moderators who identify and eliminate hate speech. However, given the large number of comments, an appropriately large number of people are required to do this work. The rapid development of artificial intelligence in the language technology area may be the solution to this problem. Automated hate speech detection would allow to manage the ever-increasing amount of online content, therefore we report hate speech classification for Lithuanian language by application of deep learning.
ISSN:2312-3125
2312-931X