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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
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
From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset—0
Toward Qualitative Evaluation of Embeddings for Arabic Sentiment Analysis—0
An Arabic Tweets Sentiment Analysis Dataset (ATSAD) using Distant Supervision and Self Training—0
Metaphorical Expressions in Automatic Arabic Sentiment Analysis—0
Sentiment Analysis for Arabic in Social Media Network: A Systematic Mapping Study—0
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