Hate Speech Detection In Social Media with Deep Learning And Language Models

Beste Akdik; Güncel Sarıman

Makale detayları

Hate Speech Detection In Social Media with Deep Learning And Language Models

Yazarlar:

Beste Akdik | Güncel Sarıman

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Natural Language Processing | Artificial Intelligence (Other)

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.1077-1095

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001351289

pISSN:

2147-3129

Anahtar kelimeler:

Özet:

 Nowadays, hate speech has started to spread rapidly with the increasing use of social media. Such abusive discourse can cause reputation damage and adversely affect psychological health. Large social media companies are trying to prevent this situation and increase their service quality with the increasing number of users every day. In this context, our study proposes a system that detects hate speech in texts and warns the user against hate speech. The project was implemented using machine learning, deep learning and language modeling techniques with a labeled hate speech dataset collected from various sources. The results show that BERTweet and DistilBERT language models achieved 90 accuracy. On the other hand, although the success of the classical models was lower, they were more effective temporally.

 Nowadays, hate speech has started to spread rapidly with the increasing use of social media. Such abusive discourse can cause reputation damage and adversely affect psychological health. Large social media companies are trying to prevent this situation and increase their service quality with the increasing number of users every day. In this context, our study proposes a system that detects hate speech in texts and warns the user against hate speech. The project was implemented using machine learning, deep learning and language modeling techniques with a labeled hate speech dataset collected from various sources. The results show that BERTweet and DistilBERT language models achieved 90 accuracy. On the other hand, although the success of the classical models was lower, they were more effective temporally.

 Nowadays, hate speech has started to spread rapidly with the increasing use of social media. Such abusive discourse can cause reputation damage and adversely affect psychological health. Large social media companies are trying to prevent this situation and increase their service quality with the increasing number of users every day. In this context, our study proposes a system that detects hate speech in texts and warns the user against hate speech. The project was implemented using machine learning, deep learning and language modeling techniques with a labeled hate speech dataset collected from various sources. The results show that BERTweet and DistilBERT language models achieved 90 accuracy. On the other hand, although the success of the classical models was lower, they were more effective temporally.

 Nowadays, hate speech has started to spread rapidly with the increasing use of social media. Such abusive discourse can cause reputation damage and adversely affect psychological health. Large social media companies are trying to prevent this situation and increase their service quality with the increasing number of users every day. In this context, our study proposes a system that detects hate speech in texts and warns the user against hate speech. The project was implemented using machine learning, deep learning and language modeling techniques with a labeled hate speech dataset collected from various sources. The results show that BERTweet and DistilBERT language models achieved 90 accuracy. On the other hand, although the success of the classical models was lower, they were more effective temporally.

Makale detayları

Hate Speech Detection In Social Media with Deep Learning And Language Models

Yazarlar: Beste Akdik | Güncel Sarıman

Yayıncı: Bitlis Eren University

Ana Başlıklar: Natural Language Processing | Artificial Intelligence (Other)

Dergi: Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.1077-1095

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001351289

pISSN: 2147-3129

Natural Language Processing

Hate Speech

Deep Learning

Language Model

Sayı

Yazarlar:

Beste Akdik | Güncel Sarıman

Yayıncı:

Bitlis Eren University

Ana Başlıklar:

Natural Language Processing | Artificial Intelligence (Other)

Dergi:

Bitlis Eren Üniversitesi Fen Bilimleri Dergisi Vol.14 Issue 2, pp.1077-1095

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001351289

pISSN:

2147-3129