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.

Opinion Analysis Based on a Sentiment Lexical Ontology and Deep Learning Models: Tunisian Dialect Case

Créateur:
TahRahLam
Éditeur:
Spr
Hôte:

Visit

doi.org

Tasks

sentiment analysistext classification

Languages

Arabic, Tunisian Spoken

Licenses

https://www.springernature.com/gp/researchers/text-and-data-mininghttps://www.springernature.com/gp/researchers/text-and-data-mining

Similaires

DZ-OPINION: Algerian Dialect Opinion Analysis Model with Deep Learning TechniquesSocial Media Sentiment Classification for Tunisian Dialect: A Deep Learning ApproachDeep Learning-Based Sentiment Analysis of Algerian Dialect during Hirak 2019Tunisian Dialect Resources for Opinion Analysis on Social MediaAUTOMATED SPEECH SENTIMENT ANALYSIS FOR MOROCCAN DIALECT SPEAKERS USING DEEP LEARNING AND MFCC-BASED FEATURESA Code-Switched Arabic-English Sentiment Analysis Approach Based on Deep-Learning

DZ-OPINION: Algerian Dialect Opinion Analysis Model with Deep Learning Techniques

Today, many sources of unstructured information such as social networks and blogs are more or less f

Social Media Sentiment Classification for Tunisian Dialect: A Deep Learning Approach

Deep Learning-Based Sentiment Analysis of Algerian Dialect during Hirak 2019

Tunisian Dialect Resources for Opinion Analysis on Social Media

AUTOMATED SPEECH SENTIMENT ANALYSIS FOR MOROCCAN DIALECT SPEAKERS USING DEEP LEARNING AND MFCC-BASED FEATURES

Abstract Sentiment analysis is used in several fields, such as teleconsultations in the medical fie

A Code-Switched Arabic-English Sentiment Analysis Approach Based on Deep-Learning