A survey on sentiment analysis and its applications
TA Al-Qablan, MH Mohd Noor, MA Al-Betar… - Neural Computing and …, 2023 - Springer
Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …
Facebook, and Instagram has become a very important task at present. Analyzing the …
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 …
A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets
Abstract Undoubtedly, coronavirus (COVID-19) has caused one of the biggest challenges of
all times. The ongoing COVID-19 pandemic has caused more than 150 million infected …
all times. The ongoing COVID-19 pandemic has caused more than 150 million infected …
Sentimental analysis of twitter data with respect to general elections in India
A Sharma, U Ghose - Procedia Computer Science, 2020 - Elsevier
It is known that social media is one of the largest sources of unstructured data. Analyzing
that data and harvesting meaning out of that is a tedious job. Recently opinion mining has …
that data and harvesting meaning out of that is a tedious job. Recently opinion mining has …
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 …
An efficient hybrid filter and evolutionary wrapper approach for sentiment analysis of various topics on Twitter
Sentiment Analysis is currently considered as one of the most attractive research topics in
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
FlexGraph: a flexible and efficient distributed framework for GNN training
Graph neural networks (GNNs) aim to learn a low-dimensional feature for each vertex in the
graph from its input high-dimensional feature, by aggregating the features of the vertex's …
graph from its input high-dimensional feature, by aggregating the features of the vertex's …
A deep learning approach for robust detection of bots in twitter using transformers
D Martín-Gutiérrez, G Hernández-Peñaloza… - IEEE …, 2021 - ieeexplore.ieee.org
During the last decades, the volume of multimedia content posted in social networks has
grown exponentially and such information is immediately propagated and consumed by a …
grown exponentially and such information is immediately propagated and consumed by a …
AI-assisted deep NLP-based approach for prediction of fake news from social media users
GG Devarajan, SM Nagarajan… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Social networking websites are now considered to be the best platforms for the
dissemination of news articles. However, information sharing in social media platforms leads …
dissemination of news articles. However, information sharing in social media platforms leads …
An efficient approach for sentiment analysis using machine learning algorithm
A Naresh, P Venkata Krishna - Evolutionary intelligence, 2021 - Springer
Sentimental analysis determines the views of the user from the social media. It is used to
classify the content of the text into neutral, negative and positive classes. Various …
classify the content of the text into neutral, negative and positive classes. Various …