STRESS ANALYSIS ON SOCIAL INTERACTIONS ON SOCIAL NETWORKING SITES USING MACHINE AND DEEP LEARNING HYBRID CLASSIFICATION

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

STRESS ANALYSIS ON SOCIAL INTERACTIONS ON SOCIAL NETWORKING SITES USING MACHINE AND DEEP LEARNING HYBRID CLASSIFICATION
Author(s):
VASAM DIVYA MOUNIKA, M. CHIRANJEEVI
Keywords:
Stress detection, factor graph model, micro-blog, social media, healthcare, social interaction
Abstract
Social media currently plays an important role in current social structure of humanity. People are used to sharing their daily activities and interacting with friends on social media platforms which provides a unique opportunity with mining, measuring, modeling different user behavioural patterns. The project is based on the idea of detecting the users stress in a proactive manner. The proposed system uses ensemble learning model which gives better accuracy compared to other standard machine learning models with the help of meta classifier and the applied algorithms are KNN, Random Forest, Convolution Neural Network, Support Vector Machine.
Article Details
Unique Paper ID: 153330 Publication Volume & Issue: Volume 8, Issue 6 Page(s): 452 - 459
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