Text Based Stress Detection Techniques Analysis Using Social Media

Psychological stress is threatening people’s health. It is mandatory to detect stress timely for proactive care. Because popularity of social media, people share their daily activities and interact with friends and family on social media platforms, which makes it feasible to leverage online social network data for stress detection. This stress detection can be done from textual data , facial expression , video and audio. This paper reviews the research approaches used in stress detection using social media. In this paper we are focusing on stress detection using textual data such as tweet, comments ,chats etc. This work focuses on techniques used for stress detection using textual data. [1][2]In this paper, we find Bidirectional Long Short-Term Memory (BLSTM) with attention mechanism to classify psychological stress and categorize the tweets based on their hashtag content gives the best performance .