• Abhilash MS
• Athmaranjan K
• Akshaya UG
• Meghana KS
• Sanjana BM

One of the key psychological conditions that causes us to experience mental or bodily pain is stress. Stress can cause both emotional and physical health problems if we are unable to manage it. Owing to the lengthy history of social isolation, lockdown, fear, mistrust, etc., almost everyone entered the stressed period. In the last three years, online gaming has gained popularity as a substitute for physical activity. Anything that people see in their personal lives can be posted online. On social media, it's customary to analyze, judge, inspire, or identify emotions. Investigating sentiment from social media messages and identifying anxiousness in a group of people based on what they share on their profiles are the goals of this study. This work is divided into two sections: detection using machine learning and data extraction using NLP techniques. The four main stages in this framework are text mining, stress detection, auto summarization, and gathering content from social media. An internet user's mental stress or overload may be lessened by the new paradigm. The new model has employed several types of machine learning algorithms in contrast to earlier approaches. Positive outcomes from the SVM model include a 90% recall rate, 94% precision, and an F1 score that is getting close to 92%. In terms of early stress detection, the new paradigm would benefit society.

Stress Recognition, NLP Techniques, ML Methods, ICON Conference 2022, WNLPe-Health Workshop 2022

"Stress Identification System using NLP and Machine Learning Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.169-175, July-2025, Available :http://www.jetir.org/papers/JETIRGX06031.pdf

"Stress Identification System using NLP and Machine Learning Approaches", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp169-175, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06031.pdf