Stress Detection Using Natural Language Processing And Machine Learning

Registration ID: IJNRD_205327

Published ID: IJNRD2309181

DOI: Click Here to Get

Jerripotula Priyanka , Prof. K. Venkata Rao

NLP, KNN, SVM, Navie Bayes, Random Forest

Nowadays many users posts tweets based on their mental condition about the things that happen in their day to day lives on the social media platforms. It is very important to detect and manage stress before it goes into a severe problem. A huge number of informal messages are posted every day in social networking sites, blogs and discussion forums. This paper describes an approach to detect the stress using the information from social media networking sites, like twitter. This project performs the operations involving data collection, data cleaning, training the machine and predicting the stressed and non-stressed users. This will be using the Natural Language Processing (NLP) and Machine Learning algorithms which include KNN ,Naïve bayes BernoulliNB, Random Forest, Decision tree and SVM. Psychological stress is threatening people’s health. It is non-trivial to detect stress timely for proactive care. With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverage online social network data for stress detection. In this paper, we find that users stress state is closely related to that of his/her friends in social media, and we employ a large-scale dataset from real-world social platforms to systematically study the correlation of users stress states and social interactions. We first define a set of stress-related textual undergoes the training of the machine followed by the machine learning algorithms for better results. Thus the proposed system takes the tweets as input and decides whether it is stressed or non-stressed.

Published Paper   E-Certificate

Jerripotula Priyanka & Prof. K. Venkata Rao (September-2023). Stress Detection Using Natural Language Processing And Machine Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(9), b720-b727. https://ijnrd.org/papers/IJNRD2309181.pdf

Volume 8 Issue 9, September-2023

Pages : b720-b727

Paper Reg. ID: IJNRD_205327

Published Paper Id: IJNRD2309181

Downloads: 000121991

Research Area: Engineering

Country: Visakhapatnam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2309181.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2309181

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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