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

VASAM DIVYA MOUNIKA; M. CHIRANJEEVI

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

Authors: VASAM DIVYA MOUNIKA, M. CHIRANJEEVI

Unique Paper ID: 153330
Volume: 8
Issue: 6
PageNo: 452-459

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.

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ISSN: 2349-6002
Volume: 8
Issue: 6
PageNo: 452-459

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

Available:https://ijirt.org/Article?manuscript=153330

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UGC Approved
Journal no 47859

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