Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Analyzing Digital Polarization on Hijab : A Dataset of Annotated YouTube Comments

Domaine:

natural language processing

Type de record:

dataset
Créateur:
Al
Éditeur:
Man
Hôte:avatar
This thesis presents a pioneering analysis of digital polarization on the topic of Hijab by examining YouTube comments from the Arab world. Employing a novel dataset of around 10K annotated comments, this research investigates the digital discourse using seven labels: Stance, Use of Sarcasm, Argumentation, Cordiality, Offensiveness, Hopefulness, and Apparent Gender of Commenters. The findings reveal significant insights into gender dynamics and the prevalence of specific rhetorical strategies within the debate. This study contributes to the broader field of polarization and argument mining, offering a unique lens on the intersection of digital culture and societal issues in the Arab context.

Visit

doi.orgmanara.qnl.qa

Tags

Human society

Licenses

In Copyrighthttp://rightsstatements.org/vocab/InC/1.0/

Similaires

Indonesian YouTube Comments DatasetAmharic Youtube Comments SentimentAbdelhamidElKrem/Darija-Sentiment-Analysis-of-YouTube-CommentsA Qualitative Inquiry into the South African Language Identifier’s Performance on YouTube Comments.bellakhdarOmaima/Darija-NLP--Sentiment-Analysis-of-YouTube-CommentsMulti-Dimensional Insights: Annotated Dataset of Stance, Sentiment, and Emotion in Facebook Comments on Tunisia's July 25 Measures

Indonesian YouTube Comments Dataset

Dataset ini berisi 5.291 komentar YouTube berbahasa Indonesia yang telah melalui tahapan preprocessi

Amharic Youtube Comments Sentiment

Movie Review Comments

AbdelhamidElKrem/Darija-Sentiment-Analysis-of-YouTube-Comments

REAL-TIME DATA PROCESSING FOR SENTIMENT ANALYSIS OF MOROCCAN DIALECT IN YOUTUBE # Big-Data

A Qualitative Inquiry into the South African Language Identifier’s Performance on YouTube Comments.

bellakhdarOmaima/Darija-NLP--Sentiment-Analysis-of-YouTube-Comments

# 📊 Project-NLP: Sentiment Analysis for YouTube Comments 🎥 ## General Description Project-NLP is an

Multi-Dimensional Insights: Annotated Dataset of Stance, Sentiment, and Emotion in Facebook Comments on Tunisia's July 25 Measures

A corpus of 7,535 Facebook comments from the Tunisian presidency page, with 5,000