Sentiment analysis (SA) is a continuing field of research that lies at the intersection of many
fields such as data mining, natural language processing and machine learning. It is …

With the recently grown attention from different research communities for opinion mining,
there is an evolving body of work on Arabic Sentiment Analysis (ASA). This paper introduces …

Social media networks have grown exponentially over the last two decades, providing the
opportunity for users of the internet to communicate and exchange ideas on a variety of …

Sentiment analysis is an area that gains wide interest from research because of its
importance and advantages in various fields. Different approaches and techniques are used …

Opinion-mining or sentiment analysis continues to gain interest in industry and academics.
While there has been significant progress in develo** models for sentiment analysis, the …

Sentiment analysis on social media platforms (ie, Twitter or Facebook) has become an
important tool to learn about users' opinions and preferences. However, the accuracy of …

In this paper, we propose a semi-supervised approach for sentiment analysis of Arabic and
its dialects. This approach is based on a sentiment corpus, constructed automatically and …

Over the past few years, much work has been done to develop machine learning models
that perform Arabic sentiment analysis (ASA) tasks at various levels and in different …

To determine whether a document or a sentence expresses a positive or negative sentiment,
three main approaches are commonly used: the lexicon-based approach, corpus-based …

Deep learning (DL) is a machine learning (ML) subdomain that involves algorithms taken
from the brain function named artificial neural networks (ANNs). Recently, DL approaches …