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@article{155125,
        author = {Suguna.n and Indirani.G},
        title = {Predicting Suicidal Behaviour Analysis using Deep Learning Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {1500-1506},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155125},
        abstract = {In 2019 survey, according to WHO, every year close to 8,00,000  people who attempt suicide. Suicide remains the second leading cause of death among a young generation with an overall suicide rate of 10.5 per 100,000 people. It is predicted that by 2020, the death rate will increase to one every 20. Almost 69% of the suicides occur in low and middle-income countries. 
It mainly aims to predict the suicidal behavior based on posts in social media websites like reddit, tweeter etc,. The early detection of suicide through Deep learning[3] and classification approaches applied to Reddit social media. For such purpose, we employ an Bi-LSTM-CNN combined neural network to evaluate and compare to other classification models.
 Our experimental results shows the combined neural network  with word embedding techniques can achieve the best result. Additionally, our result support and strengthen the ability of deep learning architectures to predict the suicidal behaviour.},
        keywords = {Suicidal ideation , Mental disorder},
        month = {},
        }