Suyash Dabhane’s scientific contributions

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Publications (2)


Depression Detection on Social Media using Machine Learning Techniques
  • Article
  • Full-text available

June 2021

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1,801 Reads

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6 Citations

Suyash Dabhane

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Depression is a common but serious mental health disorder. Still, most people dealing with depression do not approach doctors for this problem. On the other hand, the use of Social Media Sites like Twitter is expanding extremely fast. Nowadays, people tend to rely on these social media platforms to share their emotions and feelings through their feed. Thus, this readily available content on social media has become helpful for us to analyse the mental health of such users. We can apply various machine learning techniques on this social media data to extract the mental health status of a user focusing on Depression. Detecting texts that express negativity in the data is one of the best ways to detect depression. In this paper, we highlighted this problem of depression and discussed various techniques on how to detect it. we implemented a system that can detect if a person on social media is going through depression or not by analysing the user's data and activities by using various machine learning techniques.

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Depression Detection on Social Media using Machine Learning Techniques: A Survey

February 2021

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2,168 Reads

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10 Citations

Depression is a common but serious mental health disorder. Still, most people dealing with depression do not approach doctors for this problem. On the other hand, the use of Social Media Sites like Twitter is expanding extremely fast. Nowadays, people tend to rely on these social media applications to share their emotions and feelings. Thus, this readily available content has become helpful for us to analyze the mental health of such users. We can apply various machine learning techniques on social media data to extract the mental health status of a user focusing on Depression. Detecting texts that express negativity in the data is one of the best ways to detect depression. In this paper, this problem of depression detection on social media and various machine learning algorithms that can be used to detect depression have been discussed. The Ensemble Learning approach for solving this problem has been enlightened. We aim to find and implement the most appropriate approach and algorithm to solve this problem.

Citations (2)


... As well as Suyash Dabhane et al [24] whose studied the impact of implementing algorithms individually and implementing ensemble learners. The models have been training one by one, and gured out how accurate they were. ...

Reference:

Cross-Lingual Depression Detection for Twitter Users: A Comparative Sentiment Analysis of English and Arabic Tweets
Depression Detection on Social Media using Machine Learning Techniques

... Disclosure of demoralization from facial features ought to be conceivable by assessing 'Multi-Scale Entropy' (MSE) on the patient gathering video. [4] MSE helps with finding the assortments that occur across a single pixel in the video. The entropy levels of significantly expressive, non-deterred patients were high. ...

Depression Detection on Social Media using Machine Learning Techniques: A Survey