India is a hotspot of the COVID-19 crisis. During the first wave, several lockdowns (L) and
gradual unlock (UL) phases were implemented by the government of India (GOI) to curb the …

Lexical sentiment analysis (LSA) is of central importance in extracting and analyzing user
moods and views on the Web. Most existing LSA approaches have utilized supervised …

The recent wave of elections won by right-wing worldwide brings up increased discussions
biased by political polarization, including in social media. Social media data enables the …

Tweeting Brexit presents the most thorough examination of the role that the most political
social network, Twitter, played in creating, negotiating, and challenging Brexit narratives …

Twitter is a microblogging site where clients read and compose short messages on different
points each day. Political investigation using social media is getting the consideration of …

Lexical sentiment analysis (LSA) underlines a family of methods combining natural
language processing, machine learning, or graph navigation techniques to identify the …

[Objective] User groups are the main units to disseminate public opinion. This study
identifies the characteristics of user groups through clustering techniques, which could help …

Comments on Online Social Networks (OSN) contain hidden information about the quality of
teaching and learning. However, it takes a lot of time and effort to read these texts item by …

Coclustering approaches for grouping data points and features have recently been receiving
extensive attention. In this paper, we propose a constrained dual graph regularized …

Lexical sentiment analysis (LSA) is of central importance in extracting and analyzing user
moods and views on the Web. Most existing LSA approaches have utilized supervised …