The analysis of consumer sentiment, as expressed through reviews, can provide a wealth of
insight regarding the quality of a product. While the study of sentiment analysis has been …

Multimodal emotion classification (MEC) involves analyzing and identifying human emotions
by integrating data from multiple sources, such as audio, video, and text. This approach …

The influence of Large Language Models (LLMs) is rapidly growing, automating more jobs
over time. Assessing the fairness of LLMs is crucial due to their expanding impact. Studies …

The ever-evolving global landscape of communication, driven by Information Technology
advancements, underscores the importance of emotion detection in natural language …

This paper describes the system of the LowResource Team for Task 2 of BLP-2023, which
involves conducting sentiment analysis on a dataset composed of public posts and …

Sentiment Analysis (SA) refers to the task of associating a view polarity (usually, positive,
negative, or neutral; or even fine-grained such as slightly angry, sad, etc.) to a given text …

In this paper, we introduce ExMute, an extended dataset for classifying hateful memes that
incorporates critical contextual information, addressing a significant gap in existing …

The broad use of digital and Internet forums has recently facilitated various discussions and
movements, including those centered on feminism. The escalation in online participation …

Multimodal emotion classification (MEC) involves analyzing and identifying human emotions
by inte‑grating data from multiple sources, such as audio, video, and text. This approach …