Sentiment analysis in social media data for depression detection using artificial intelligence: a review
NV Babu, EGM Kanaga - SN computer science, 2022 - Springer
Sentiment analysis is an emerging trend nowadays to understand people's sentiments in
multiple situations in their quotidian life. Social media data would be utilized for the entire …
multiple situations in their quotidian life. Social media data would be utilized for the entire …
Machine learning techniques for sentiment analysis of COVID-19-related twitter data
N Braig, A Benz, S Voth, J Breitenbach… - IEEE Access, 2023 - ieeexplore.ieee.org
On Twitter, COVID-19 is a highly discussed topic. People worldwide have used Twitter to
express their viewpoints and feelings during the pandemic. Previous research has focused …
express their viewpoints and feelings during the pandemic. Previous research has focused …
A deep learning-based model using hybrid feature extraction approach for consumer sentiment analysis
There is an exponential growth in textual content generation every day in today's world. In-
app messaging such as Telegram and WhatsApp, social media websites such as Instagram …
app messaging such as Telegram and WhatsApp, social media websites such as Instagram …
An aspect sentiment classification model for graph attention networks incorporating syntactic, semantic, and knowledge
S Zhang, H Gong, L She - Knowledge-Based Systems, 2023 - Elsevier
Aspect sentiment classification tasks aim to identify the aspect in a sentence and express the
sentiment polarities of the aspect. In existing studies, combining different deep learning …
sentiment polarities of the aspect. In existing studies, combining different deep learning …
Confidence-aware sentiment quantification via sentiment perturbation modeling
Sentiment Quantification aims to detect the overall sentiment polarity of users from a set of
reviews corresponding to a target. Existing methods equally treat and aggregate individual …
reviews corresponding to a target. Existing methods equally treat and aggregate individual …
A survey of sentiment analysis from film critics based on machine learning, lexicon and hybridization
Recent research and developments in the field of Sentiment Analysis (SA) have made it
possible to simplify the detection and classification of sentiments from the textual content …
possible to simplify the detection and classification of sentiments from the textual content …
Testing and analysis of predictive capabilities of machine learning algorithms
The use of machine learning algorithms in last decade has been enormously increased. It
has opened the door to several opportunities in various fields of research and business …
has opened the door to several opportunities in various fields of research and business …
Deep-Sentiment: An Effective Deep Sentiment Analysis Using a Decision-Based Recurrent Neural Network (D-RNN)
P Durga, D Godavarthi - IEEE Access, 2023 - ieeexplore.ieee.org
Sentiment analysis is a sub-domain in opinion mining that extracts sentiments from the
users' opinions from text messages. Opinions from E-commerce websites, blogs, online …
users' opinions from text messages. Opinions from E-commerce websites, blogs, online …
Tweet sentiment quantification: An experimental re-evaluation
A Moreo, F Sebastiani - PLoS One, 2022 - journals.plos.org
Sentiment quantification is the task of training, by means of supervised learning, estimators
of the relative frequency (also called “prevalence”) of sentiment-related classes (such as …
of the relative frequency (also called “prevalence”) of sentiment-related classes (such as …
Experimental performance analysis of machine learning algorithms
Abstract Machine Learning models and algorithms have become quite common these days.
Deep Learning and Machine Learning algorithms are utilized in various projects, and now, it …
Deep Learning and Machine Learning algorithms are utilized in various projects, and now, it …