Introduction Several attempts have been made to enhance text-based sentiment analysis's
performance. The classifiers and word embedding models have been among the most …

This paper proposes a novel hybrid model for sentiment analysis. The model leverages the
strengths of both the Transformer model, represented by the Robustly Optimized BERT …

The unprecedented growth in the use of social media platforms, where opinions and
decisions are made and updated within seconds. Hence, Twitter is becoming a huge …

Due to the rapid development of technology, social media has become more and more
common in human daily life. Social media is a platform for people to express their feelings …

A massive use of social media platforms such as Twitter and Facebook by omnifarious
organizations has increased the critical individual feedback on the situation, events …

Various attempts have been conducted to improve the performance of text-based sentiment
analysis. These significant attempts have focused on text representation and model …

Sentiment analysis is considered as one of the most essential tasks in the field of natural
language processing and cognitive science. In order to enhance the performance of …

Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …

Sentiment analysis is a challenging task in natural language processing, especially for
social media texts, which are often informal, short, and noisy. In this paper, we present a …

As data grow rapidly on social media by users' contributions, specially with the recent
coronavirus pandemic, the need to acquire knowledge of their behaviors is in high demand …