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 …
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 …
A robust sentiment analysis method based on sequential combination of convolutional and recursive neural networks
With explosive development of the World Wide Web, an enormous amount of text
information containing users' feeling, emotions and opinions has been generated and is …
information containing users' feeling, emotions and opinions has been generated and is …
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 …
[PDF][PDF] Sentiment analysis using deep learning techniques: a review
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 …
An efficient sentiment analysis methodology based on long short-term memory networks
Sentiment analysis is the process of determining the sentiment polarity (positivity, neutrality
or negativity) of the text. As online markets have become more popular over the past …
or negativity) of the text. As online markets have become more popular over the past …
User reviews: Sentiment analysis using lexicon integrated two-channel CNN–LSTM family models
Sentiment analysis, which refers to the task of detecting whether a textual item (eg, a product
review and a blog post) expresses a positive or negative opinion in general or about a given …
review and a blog post) expresses a positive or negative opinion in general or about a given …
[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 …
Exploration of social media for sentiment analysis using deep learning
LC Chen, CM Lee, MY Chen - Soft Computing, 2020 - Springer
With the rapid growth of web content from social media, such studies as online opinion
mining or sentiment analysis of text have started receiving attention from government …
mining or sentiment analysis of text have started receiving attention from government …
Spider monkey crow optimization algorithm with deep learning for sentiment classification and information retrieval
The epidemic increase in online reviews' growth made the sentiment classification a
fascinating domain in academic and industrial research. The reviews assist several …
fascinating domain in academic and industrial research. The reviews assist several …