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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
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
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