• PATCHALA.SRINIVAS
• GOLI.RANGHANADHA RAO

Psychological strain is threatening human’s fitness. It is non-trivial to locate stress properly timed for proactive care. With the recognition of social media, humans are used to sharing each day sports activities and interacting with friends on social media platforms, making it viable to leverage on-line social network information for pressure detection. In this paper, we find that clients strain nation is carefully associated with that of his/her buddies in social media, and we lease a huge-scale dataset from real-global social systems to systematically take a look at the correlation of clients’ stress states and social interactions. We first define a fixed of stress-related textual, seen, and social attributes from several aspects, after which propose a completely unique hybrid version - a component graph model combined with Convolutional Neural Network to leverage tweet content material and social interplay records for strain detection. Experimental effects show that the proposed model can enhance the detection overall performance via manner of 6-nine% in F1-score. By further analyzing the social interplay information, we additionally discover numerous intriguing phenomena, i.e. The range of social systems of sparse connections (i.e. And not using a delta connections) of compelled customers is around 14% higher than that of non-burdened customers, indicating that the social shape of careworn users’ pals tends to be much less connected and much less complex than that of non-confused customers.

Stress detection, factor graph model, micro-blog, social media, healthcare, social interaction.

"DIGITAL COMMUNICATION BASED STRESS DISCOVERY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.741-744, June-2018, Available :http://www.jetir.org/papers/JETIR1806228.pdf

"DIGITAL COMMUNICATION BASED STRESS DISCOVERY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp741-744, June-2018, Available at : http://www.jetir.org/papers/JETIR1806228.pdf