sai dixit | Georgia State University (original) (raw)
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Traditional mental health studies depend on information primarily collected through personal cont... more Traditional mental health studies depend on information primarily collected through personal contact with the health care professional. Recent work has shown that the pervasiveness of social media provides a great opportunity to study depression and to enhance the data available to mental health clinicians and researches, enabling a better-informed and better-equipped mental health field. We present analysis of mental health phenomena in publicly available twitter data, using deep neural networks with Convolutional Neural Network layer and Long Short Term Memory Neural Network layer. We demonstrate it's utility by examining differences in language use between the random individuals tweets with positive tweets and negative/depressive tweets. Finally, Twitter data can be an effective tool to analyze the mental health of the people and can be the replacement for the traditional survey methods.
Traditional mental health studies depend on information primarily collected through personal cont... more Traditional mental health studies depend on information primarily collected through personal contact with the health care professional. Recent work has shown that the pervasiveness of social media provides a great opportunity to study depression and to enhance the data available to mental health clinicians and researches, enabling a better-informed and better-equipped mental health field. We present analysis of mental health phenomena in publicly available twitter data, using deep neural networks with Convolutional Neural Network layer and Long Short Term Memory Neural Network layer. We demonstrate it's utility by examining differences in language use between the random individuals tweets with positive tweets and negative/depressive tweets. Finally, Twitter data can be an effective tool to analyze the mental health of the people and can be the replacement for the traditional survey methods.