Psychological Stress Prediction on Social Media using Convolutional Neural Network
Preethi Rajam C. R1, Uma Maheswari N2, Jeyanthi S3, Somasundaram S. K4
1Preethi Rajam C. R, PG Scholar, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
2Uma Maheswari N, Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
3Jeyanthi S, Assistant Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
4Somasundaram S. K, Associate Professor, Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul (Tamil Nadu), India.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3464-3468 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B15830982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1583.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Psychological stress which is a mental illness also causes physical problems to the human. Nowadays social media plays an important role in the world for communication to share their thoughts with their friends and family. The social media analysis is the process of detecting and predicting the user’s thoughts and opinions which also one of the important perspective in the developing business environment. The overwhelming stress and long term stress sometimes lead to suicidal ideation. By analyzing the social media content to predict the overwhelming stress state of the users in the earlier stage will reduce the psychological stress and suicidal rate too. In this paper, we address the problem of stress prediction by using social media. The machine learning and deep learning methods to perform the classification of stress analysis. Here both image and text- tweet data are used and the images are processed with the Optical Character Recognition and the text data are processed by using the Natural Language Processing and Convolutional Neural Network for classifying the tweet content of the user as stressed or non-stressed. Furthermore, with the advancement of the machine learning and deep learning method of classification gives a better result in terms of performance and accuracy of the prediction.
Keywords: Social Media, Machine Learning, Natural Language Processing, Convolutional Neural Network.
Scope of the Article: Social Networks