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Arabic Sentiment Analysis

Arabic sentiment analysis is the process of computationally identifying and categorizing opinions expressed in a piece of arabic text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral (Source: Oxford Languages)

Papers

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Showing 1–25 of 42 papers

TitleStatusHype
Advancing Arabic Sentiment Analysis: ArSen Benchmark and the Improved Fuzzy Deep Hybrid NetworkCode0
ArSen-20: A New Benchmark for Arabic Sentiment DetectionCode0
Arabic Text Sentiment Analysis: Reinforcing Human-Performed Surveys with Wider Topic Analysis—0
Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter—0
Arabic Sentiment Analysis with Noisy Deep Explainable Model—0
Multilevel sentiment analysis in arabic—0
A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment DatasetsCode0
Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis—0
Overview of the Arabic Sentiment Analysis 2021 Competition at KAUST—0
Negation Handling in Machine Learning-Based Sentiment Classification for Colloquial Arabic—0
Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language—0
Effect of Word Embedding Variable Parameters on Arabic Sentiment Analysis Performance—0
ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset—0
A review of sentiment analysis research in Arabic language—0
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language ProcessingCode1
Toward Qualitative Evaluation of Embeddings for Arabic Sentiment Analysis—0
Metaphorical Expressions in Automatic Arabic Sentiment Analysis—0
From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset—0
An Arabic Tweets Sentiment Analysis Dataset (ATSAD) using Distant Supervision and Self Training—0
Sentiment Analysis for Arabic in Social Media Network: A Systematic Mapping Study—0
hULMonA: The Universal Language Model in ArabicCode0
Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects—0
Mazajak: An Online Arabic Sentiment Analyser—0
Empirical Evaluation of Leveraging Named Entities for Arabic Sentiment Analysis—0
A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector MachineCode0
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