Sentiment analysis has proven to be a valuable tool to gauge public opinion in different
disciplines. It has been successfully employed in financial market prediction, health issues …

Sentiment analysis is a critical subfield of natural language processing that focuses on
categorizing text into three primary sentiments: positive, negative, and neutral. With the …

The social and behavioral sciences have been increasingly using automated text analysis to
measure psychological constructs in text. We explore whether GPT, the large-language …

Sentiment analysis (SA) has been a long-standing research area in natural language
processing. It can offer rich insights into human sentiments and opinions and has thus seen …

Despite its importance, the time variable has been largely neglected in the NLP and
language model literature. In this paper, we present TimeLMs, a set of language models …

Sentiment analysis is an essential task in natural language processing that involves
identifying a text's polarity, whether it expresses positive, negative, or neutral sentiments …

This study presents a thorough examination of various Generative Pretrained Transformer
(GPT) methodologies in sentiment analysis, specifically in the context of Task 4 on the …

The experimental landscape in natural language processing for social media is too
fragmented. Each year, new shared tasks and datasets are proposed, ranging from classics …

The release of ChatGPT has uncovered a range of possibilities whereby large language
models (LLMs) can substitute human intelligence. In this paper, we seek to understand …

Pre-trained language models (LMs) are currently integral to many natural language
processing systems. Although multilingual LMs were also introduced to serve many …