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Cross-lingual embeddings for hate speech detection in comments
Marinšek, Rok (Author), Robnik Šikonja, Marko (Mentor) More about this mentor... This link opens in a new window, Fraser, Alexander M. (Co-mentor)

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Abstract
With the recent explosion of social media content, the amount of online hate speech is increasing, making it impossible to filter it manually. For automatic hate speech detection, a lot of annotated data is needed, which is mostly available for high-resource languages. In spite of data scarcity in low-resource languages, we want to detect hate speech in those languages. We use cross-lingual embeddings to achieve an acceptable performance in hate speech detection in a target language, using data from another language. We use hate speech comments from English, German, and Croatian. We use fastText word embeddings, align them with the RCSLS method, and achieve reasonable performance in 2 out of 6 language pairs. With Multilingual BERT, we improve upon this method, and achieve acceptable performance in 3 out of 6 language pairs.

Language:English
Keywords:word embedding, cross-lingual embedding, deep learning, hate speech detection, natural language processing, RCSLS method, BERT language model
Work type:Master's thesis/paper (mb22)
Organization:FRI - Faculty of computer and information science
Year:2019
COBISS.SI-ID:1538458051 Link is opened in a new window
Views:615
Downloads:267
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Secondary language

Language:Slovenian
Title:Uporaba medjezičnih vektorskih vložitev za odkrivanje sovražnega govora v komentarjih
Abstract:
V zadnjih letih se je z eksplozijo vsebin na družbenih medijih povišala količina sovražnega govora. Zaradi velike količine podatkov je ročno moderiranje sovražnih vsebin nemogoče. Trenutno za avtomatsko odkrivanje sovražnega govora najpogosteje uporabljamo nevronske mreže. Za njihovo učenje je potrebno veliko označenih primerov, ki so večinoma na voljo le za večje jezike, npr. za angleščino. Označenih podatkov za manjše jezike je načeloma malo. Vseeno bi želeli tudi v teh jezikih zaznavati sovražni govor. V tem delu s pomočjo medjezikovnih vložitev razvijemo metodo, ki ob prenosu dosega sprejemljive rezultate za ciljni jezik. Komentarji s sovražnim govorom so v angleščini, nemščini in hrvaščini. Uporabimo fastText vložitve, jih poravnamo z metodo RCSLS, in dosežemo sprejemljive rezultate za dva od šestih jezikovnih parov. Z modelom BERT izboljšamo to metodo in dosežemo sprejemljive rezultate za tri od šestih jezikovnih parov.

Keywords:vektorska vložitev, medjezikovna vložitev, globoko učenje, odkrivanje sovražnega govora, obdelava naravnega jezika, metoda RCSLS, jezikovni model BERT

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