Efficiently Combining Tweet Content and Social Interactions to Enhance Stress Recognition Performance

  • G. Sushmitha Reddy, Dr. P. Neelakantan

Abstract

Mental stress is becoming a threat to people’s health today. With the rapid pace of life, more and more people are feeling stressed. Increase of stress has become a great challenge to human health and life quality. Thus, there is significant importance to detect stress before it turns into severe problems. This study defines a set of stress-related textual, visual, and social attributes from various aspects, and then propose a novel hybrid model - a factor graph model combined with Convolutional Neural Network to leverage tweet content and social interaction information for stress detection.

Published
2019-11-21
How to Cite
Dr. P. Neelakantan, G. S. R. (2019). Efficiently Combining Tweet Content and Social Interactions to Enhance Stress Recognition Performance. International Journal of Advanced Science and Technology, 28(16), 225 - 229. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/1675
Section
Articles