Sartaj Ahmad1* and Rishabh Varma2
Author Address :
1,2KIET Group of Institutions, Ghaziabad-201206, Uttar Pradesh, India.
We are living in an era of increased pressure and mental disorders. The increased level of stress and pressure results in inclination of the number of people showing suicidal tendencies and thus a larger number of people are committing suicide. Stress can be caused due to family dispute, job dissatisfaction, health issues, etc. In the world of modern computing, people feel free to share their views and feelings over social media with peers and family members via services such as messaging. Due to the reserved nature and busy schedules of people it is extremely difficult to interact with peers and family members in person, therefore social media platforms are considered as the most used platform for personal conversations. The aim of this paper is to estimate the suicidal tendencies of a person by applying data mining techniques to the text messages a person sends to the associated people. By analysing the components of the text messages (key words and emoticons) we can estimate the suicidal tendencies of a person so that necessary steps can be taken in order to save the life of the subject.
Text mining, knowledge discovery, sentiment analysis, opinion mining.
Article Info :
Received : December 24, 2017; Accepted : January 21, 2018.