[HTML][HTML] Transformer-based deep learning models for the sentiment analysis of social media data
ST Kokab, S Asghar, S Naz - Array, 2022 - Elsevier
Sentiment analysis (SA) is a widely used contextual mining technique for extracting useful
and subjective information from text-based data. It applies on Natural Language Processing …
and subjective information from text-based data. It applies on Natural Language Processing …
Improving sentiment analysis for social media applications using an ensemble deep learning language model
A Alsayat - Arabian Journal for Science and Engineering, 2022 - Springer
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 …
coronavirus pandemic, the need to acquire knowledge of their behaviors is in high demand …
Sentiment analysis using deep learning techniques: a comprehensive review
With the exponential growth of social media platforms and online communication, the
necessity of using automated sentiment analysis techniques has significantly increased …
necessity of using automated sentiment analysis techniques has significantly increased …
An intelligent cognitive-inspired computing with big data analytics framework for sentiment analysis and classification
Advancements in recent networking and information technology have always been a natural
phenomenon. The exponential amount of data generated by the people in their day-to-day …
phenomenon. The exponential amount of data generated by the people in their day-to-day …
Depression detection from social networks data based on machine learning and deep learning techniques: An interrogative survey
KM Hasib, MR Islam, S Sakib, MA Akbar… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Users can interact with one another through social networks (SNs) by exchanging
information, delivering comments, finding new information, and engaging in discussions that …
information, delivering comments, finding new information, and engaging in discussions that …
Ensemble transfer learning-based multimodal sentiment analysis using weighted convolutional neural networks
Huge amounts of multimodal content and comments in a mixture form of text, image, and
emoji are continuously shared by users on various social networks. Most of the comments of …
emoji are continuously shared by users on various social networks. Most of the comments of …
Predictive intelligence in harmful news identification by BERT-based ensemble learning model with text sentiment analysis
In an environment full of disordered information, the media spreads fake or harmful
information into the public arena with a speed which is faster than ever before. A news report …
information into the public arena with a speed which is faster than ever before. A news report …
TClustVID: A novel machine learning classification model to investigate topics and sentiment in COVID-19 tweets
Abstract COVID-19, caused by SARS-CoV2 infection, varies greatly in its severity but
presents with serious respiratory symptoms with vascular and other complications …
presents with serious respiratory symptoms with vascular and other complications …
TSA-CNN-AOA: Twitter sentiment analysis using CNN optimized via arithmetic optimization algorithm
COVID-19, a novel virus from the coronavirus family, broke out in Wuhan city of China and
spread all over the world, killing more than 5.5 million people. The speed of spreading is still …
spread all over the world, killing more than 5.5 million people. The speed of spreading is still …
Transforming sentiment analysis for e-commerce product reviews: Hybrid deep learning model with an innovative term weighting and feature selection
Improving user satisfaction by analyzing many user reviews found on e-commerce platforms
is becoming increasingly significant in this modern world. However, accurately predicting …
is becoming increasingly significant in this modern world. However, accurately predicting …