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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 26–42 of 42 papers

TitleStatusHype
SentiArabic: A Sentiment Analyzer for Standard Arabic—0
Sentiment after Translation: A Case-Study on Arabic Social Media Posts—0
Sentiment Analysis for Arabic in Social Media Network: A Systematic Mapping Study—0
Sentiment analysis for Arabic language: A brief survey of approaches and techniques—0
Sentiment Analysis For Modern Standard Arabic And Colloquial—0
Sentiment Analysis of Arabic Tweets Using Semantic Resources—0
Sentiment/Subjectivity Analysis Survey for Languages other than English—0
Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects—0
Toward Qualitative Evaluation of Embeddings for Arabic Sentiment Analysis—0
A Combined CNN and LSTM Model for Arabic Sentiment Analysis—0
Using objective words in the reviews to improve the colloquial arabic sentiment analysis—0
An Arabic Tweets Sentiment Analysis Dataset (ATSAD) using Distant Supervision and Self Training—0
Arabic Sentiment Analysis with Noisy Deep Explainable Model—0
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
ARB-SEN at SemEval-2018 Task1: A New Set of Features for Enhancing the Sentiment Intensity Prediction in Arabic Tweets—0
A review of sentiment analysis research in Arabic language—0
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