Semantic Scholar Open Access 2017 1240 sitasi

Deep Learning for Hate Speech Detection in Tweets

Pinkesh Badjatiya Shashank Gupta Manish Gupta Vasudeva Varma

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Abstrak

Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist, sexist or neither. The complexity of the natural language constructs makes this task very challenging. We perform extensive experiments with multiple deep learning architectures to learn semantic word embeddings to handle this complexity. Our experiments on a benchmark dataset of 16K annotated tweets show that such deep learning methods outperform state-of-the-art char/word n-gram methods by ~18 F1 points.

Topik & Kata Kunci

Computer Science

Penulis (4)

Pinkesh Badjatiya

Shashank Gupta

Manish Gupta

Vasudeva Varma

Format Sitasi

APA MLA BibTeX

Badjatiya, P., Gupta, S., Gupta, M., Varma, V. (2017). Deep Learning for Hate Speech Detection in Tweets. https://doi.org/10.1145/3041021.3054223

Akses Cepat

Lihat di Sumber doi.org/10.1145/3041021.3054223

Informasi Jurnal

Tahun Terbit: 2017
Bahasa: en
Total Sitasi: 1240×
Sumber Database: Semantic Scholar
DOI: 10.1145/3041021.3054223
Akses: Open Access ✓