Papers by Hammad Rizwan

2 papers
Hate-Speech and Offensive Language Detection in Roman Urdu (2020.emnlp-main)

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Challenge: Existing research on hate-speech and offensive language detection in social media content is mainly focused on the English language.
Approach: They propose to use an annotated dataset to detect hate-speech and offensive language in social media content . they propose to transfer five existing embedding models to Roman Urdu to test their performance .
Outcome: The proposed model outperforms existing methods on RUHSOLD dataset and train domain-specific embeddings on more than 4.7 million tweets.
Exploring Data Augmentation Strategies for Hate Speech Detection in Roman Urdu (2022.lrec-1)

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Challenge: a number of social media platforms are generating hateful content, a new study finds . augmentation techniques are needed to improve the performance of the models .
Approach: They evaluate different data augmentation techniques for the improvement of hate speech detection in Roman Urdu.
Outcome: The proposed techniques improve hate speech detection in Roman Urdu on two datasets.

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