2023
DOI: 10.1007/s10579-023-09642-7
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UHated: hate speech detection in Urdu language using transfer learning

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Cited by 6 publications
(2 citation statements)
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References 24 publications
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“…In 2019, an NLP group from Turku University published FinBERT, a BERT-based pretrain language model for the Finnish language [ 29 ]. The FinBERT model is reported to have better performance than other popular models, including multilingual BERT, convolutional neural networks, and long short-term memory [ 30 , 31 ].…”
Section: Methodsmentioning
confidence: 99%
“…In 2019, an NLP group from Turku University published FinBERT, a BERT-based pretrain language model for the Finnish language [ 29 ]. The FinBERT model is reported to have better performance than other popular models, including multilingual BERT, convolutional neural networks, and long short-term memory [ 30 , 31 ].…”
Section: Methodsmentioning
confidence: 99%
“…Language Objective Sub-classes/Targets Context Mossie et al [15] Facebook Amharic Hate Speech General discourse Mulki et al [16] Twitter Arabic Hate speech Politics Qian et al [20] Reddit and Gab English Hate speech General discourse Shrestha et al [29] Nepali News Portals Nepali Sentiment analysis News Media Mathew et al [13] Twitter and Gab English Hate speech Targeted Communities General discourse Armeu et al [3] Twitter Arabic Hate and Misinformation Identification COVID-19 Romim et al [23] YouTube and Facebook Bengali Hate Speech General Discourse Niraula et al [17] Facebook, Twitter, YouTube Nepali Offensive Language Sexist, Racist General discourse Toraman et al [35] Twitter Turkish, English Hate General Discourse Arshad et al [4] Twitter These keywords were selected to capture the important themes and topics related to the Nepalese local elections, including the major political parties and their representatives, election-related terminology, and other relevant keywords related to the election process. By selecting these keywords, we aim to capture a wide range of discussions and opinions related to the local elections in Nepal on social media.…”
Section: Work Data Sourcementioning
confidence: 99%