This study utilized large language models (LLMs) to analyze public sentiment in the United
States (US) regarding nuclear power on social media, focusing on X/Twitter, considering …

The interest in social media sentiment analysis and opinion mining for public security events
has increased over the years. The availability of social media platforms for communication …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Energy prices have gone up gradually since last year, but a drastic hike has been observed
recently in the past couple of months, affecting people's thrift. This, coupled with the load …

Sentic computing is a multi-disciplinary approach to sentiment analysis at the crossroads
between affective computing and commonsense computing, which exploits both computer …

Knowing the presence, attitude and sentiment of society is important to promote policies and
actions that influence the development of different energy sources and even more so in the …

This study analyzes Twitter s contribution to green energy. More than 200,000 global tweets
sent during 2020 containing the terms" green energy" OR" greenenergy" were analyzed …

This research proposes a well-being analytical framework using social media chatter data.
The proposed framework infers analytics and provides insights into the public's well-being …

The energy crisis following the Russian invasion of Ukraine has prompted affected countries
to increase efforts to save energy. Despite substantial energy conservation observed across …

abstract The interest in social media sentiment analysis and opinion mining for public
security events has increased over the years. The availability of social media platforms for …