Analyzing and understanding the sentiments of social media documents on Twitter,
Facebook, and Instagram has become a very important task at present. Analyzing the …

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 …

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 …

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 …

Improving user satisfaction by analyzing many user reviews found on e-commerce platforms
is becoming increasingly significant in this modern world. However, accurately predicting …

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 …

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 …

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 …

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 …

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 …