AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS

Yıl 2017, , 368 - 371, 30.06.2017

Xhemal Zenuni Jaumin Ajdari Florije Ismaili Bujar Raufi

https://doi.org/10.17261/Pressacademia.2017.612

Öz

Internet in general and social media in particular have
greatly facilitated the communication, interaction and collaboration among
people and different entities. As generally there is no censorship, these media
sometimes are used to proliferate discourses that contain hateful messages
targeting ethnic origin, religious or sexual groups, which potentially may
degenerate to violent acts against individuals of such groups. Therefore, we
explore the idea of building of automatic classifier that can be used for detection
of hate speech in public Albanian language pages. A hate speech corpus for
Albanian language is created, and then based on Support Vector Machine (SVM)
approach,  an automatic hate speech
detection system is proposed. Such system can be used to detect and analyze
hate speech in online contents over time and to enhance our knowledge on how
they affect opinion creation in society.  

Anahtar Kelimeler

Hate speech detection, text classification, support vector machines, NLP, Albanian language

Kaynakça

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