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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 1–10 of 42 papers

TitleStatusHype
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language ProcessingCode1
ArSen-20: A New Benchmark for Arabic Sentiment DetectionCode0
Advancing Arabic Sentiment Analysis: ArSen Benchmark and the Improved Fuzzy Deep Hybrid NetworkCode0
hULMonA: The Universal Language Model in ArabicCode0
A Deep CNN Architecture with Novel Pooling Layer Applied to Two Sudanese Arabic Sentiment DatasetsCode0
A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector MachineCode0
LABR: A Large Scale Arabic Sentiment Analysis BenchmarkCode0
Arabic Text Sentiment Analysis: Reinforcing Human-Performed Surveys with Wider Topic Analysis—0
Arabic Sentiment Analysis with Noisy Deep Explainable Model—0
A review of sentiment analysis research in Arabic language—0
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