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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 11–20 of 42 papers

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Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis—0
A System for Extracting Sentiment from Large-Scale Arabic Social Data—0
A review of sentiment analysis research in Arabic language—0
Combining Lexical Features and a Supervised Learning Approach for Arabic Sentiment Analysis—0
Effect of Word Embedding Variable Parameters on Arabic Sentiment Analysis Performance—0
ARB-SEN at SemEval-2018 Task1: A New Set of Features for Enhancing the Sentiment Intensity Prediction in Arabic Tweets—0
Des repr\'esentations continues de mots pour l'analyse d'opinions en arabe: une \'etude qualitative (Word embeddings for Arabic sentiment analysis : a qualitative study)—0
Empirical Evaluation of Leveraging Named Entities for Arabic Sentiment Analysis—0
Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language—0
Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter—0
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