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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

TitleStatusHype
ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset—0
A System for Extracting Sentiment from Large-Scale Arabic Social Data—0
From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset—0
Combining Lexical Features and a Supervised Learning Approach for Arabic Sentiment Analysis—0
Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language—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
Effect of Word Embedding Variable Parameters on Arabic Sentiment Analysis Performance—0
Empirical Evaluation of Leveraging Named Entities for Arabic Sentiment Analysis—0
Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis—0
Mazajak: An Online Arabic Sentiment Analyser—0
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