Artificial Intelligence-based Hyper Activity Analysis
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Abstract
Sentiment analysis has emerged as a valuable tool for analyzing human behavior and measuring frustration levels. This abstract provides an overview of the sentiment analysis of human behavior in response tomeasuring frustration levels. By examining the emotional tone expressed in textual data, sentiment analysis techniques offer insights into individuals’ frustration levels, contributing to a better understanding of their psychological wellbeing. This study focuses on the application of sentiment analysis in measuring frustration levels and understanding human behavior. It explores the limitations and challenges associated with accurately assessing frustration based on Textual data, Psychological Questionnaires, Image Processing, Tone or speech, and Augmented Reality. The study acknowledges the importance of context and the need to account for linguistic nuances, sarcasm, and individual differences in language use. It also emphasizes the significance of considering additional modalities, such as facial expressions and virtual reality, to enhance the accuracy and reliability of measuring frustration levels.
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