Analysis of Social Media for Psychological Stress Detection using Ontologies

The technological advancement and significant rise in the usage of social media has resulted in major psychological health problems such as stress, anxiety etc. These challenges can be analyzed and prevention strategies can be formulated. To overcome these severe problems, the urgent need is to monitor the microblogs in social media as it is irrepressible by humans due to their strong desire towards SMEs (Social Media Environments). Traditional methods such as questionnaires and interviews were conducted by psychologists but these processes are time-consuming and hysteretic. In this paper we have surveyed various stress detection strategies and found to be ineffective to detect stress from social media. In this paper we proposed an Effective Stress Detection Framework (ESDF) to utilize the hybrid ontology for stress detection among individuals and taking necessary precautions to prevent the users from committing suicide. Hybrid ontology is the keyword matching search process used in social media to identify the stress-related messages shared among individuals with improved accuracy.