A hybrid CNN-LSTM: A deep learning approach for consumer sentiment analysis using qualitative user-generated contents
With the fastest growth of information and communication technology (ICT), the availability of
web content on social media platforms is increasing day by day. Sentiment analysis from …
web content on social media platforms is increasing day by day. Sentiment analysis from …
Hybrid deep learning models for thai sentiment analysis
K Pasupa, T Seneewong Na Ayutthaya - Cognitive Computation, 2022 - Springer
Many people use social media in their daily life for entertainment, business, personal
communication, and catching up with friends. In social media marketing, sentiment analysis …
communication, and catching up with friends. In social media marketing, sentiment analysis …
[PDF][PDF] Text based sentiment analysis using LSTM
GSN Murthy, SR Allu, B Andhavarapu… - Int. J. Eng. Res …, 2020 - pdfs.semanticscholar.org
Analyzing the big textual information manually is tougher and time-consuming. Sentiment
analysis is a automated process that uses computing (AI) to spot positive and negative …
analysis is a automated process that uses computing (AI) to spot positive and negative …
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 …
Sentiment analysis of tweets using a unified convolutional neural network‐long short‐term memory network model
Sentiment analysis focuses on identifying and classifying the sentiments expressed in text
messages and reviews. Social networks like Twitter, Facebook, and Instagram generate …
messages and reviews. Social networks like Twitter, Facebook, and Instagram generate …
Roberta-Gru: A hybrid deep learning model for enhanced sentiment analysis
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 …
strengths of both the Transformer model, represented by the Robustly Optimized BERT …
[PDF][PDF] Sentiment analysis using deep learning techniques: a review
QT Ain, M Ali, A Riaz, A Noureen, M Kamran… - International Journal of …, 2017 - academia.edu
The World Wide Web such as social networks, forums, review sites and blogs generate
enormous heaps of data in the form of users views, emotions, opinions and arguments about …
enormous heaps of data in the form of users views, emotions, opinions and arguments about …
Exploiting deep learning for Persian sentiment analysis
The rise of social media is enabling people to freely express their opinions about products
and services. The aim of sentiment analysis is to automatically determine subject's sentiment …
and services. The aim of sentiment analysis is to automatically determine subject's sentiment …
A novel LSTM–CNN–grid search-based deep neural network for sentiment analysis
I Priyadarshini, C Cotton - The Journal of Supercomputing, 2021 - Springer
As the number of users getting acquainted with the Internet is escalating rapidly, there is
more user-generated content on the web. Comprehending hidden opinions, sentiments, and …
more user-generated content on the web. Comprehending hidden opinions, sentiments, and …
ACNN-TL: attention-based convolutional neural network coupling with transfer learning and contextualized word representation for enhancing the performance of …
H Sadr, M Nazari Soleimandarabi - The Journal of Supercomputing, 2022 - Springer
Due to the rapid growth of textual information on the web, analyzing users' opinions about
particular products, events or services is now considered a crucial and challenging task that …
particular products, events or services is now considered a crucial and challenging task that …