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)
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
ARABIC SENTIMENT ANALYSIS ARABIC TEXT DIACRITIZATION DIALECT IDENTIFICATION MORPHOLOGICAL ANALYSIS MORPHOLOGICAL INFLECTION NAMED ENTITY RECOGNITION
Experiment results show that the developed hULMonA and multi-lingual ULM are able to generalize well to multiple Arabic data sets and achieve new state of the art results in Arabic Sentiment Analysis for some of the tested sets.
ARABIC SENTIMENT ANALYSIS LANGUAGE MODELLING TEXT CLASSIFICATION TRANSFER LEARNING
We explore using the dataset for two tasks: (1) sentiment polarity classification; and (2) ratings classification.