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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
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language ProcessingCode1
A System for Extracting Sentiment from Large-Scale Arabic Social Data—0
Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter—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
A Combined CNN and LSTM Model for Arabic Sentiment Analysis—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
ASAD: A Twitter-based Benchmark Arabic Sentiment Analysis Dataset—0
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