Depression Detection using Sentiment Analysis |
Author(s): |
| Pranjal Girish Mahajan , Cummins College Of Engineering; Tushar B Kute, MITU Skillologies |
Keywords: |
| Text Classiï¬cation; Machine Learning; Logistic Regression; Social Media; Depression |
Abstract |
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Twitter sentiment analysis is an application of sentiment analysis on data from Twitter (tweets), in order to extract sentiments conveyed by the user. Several studies carried out have shown the correlation between social media and depression. We aim at contributing to the research on depression detection using Sentiment analysis. We have pre-processed the data, applied feature extraction and feature selection. Thereafter, we measured the performance of two machine learning algorithms: Naive Bayes and Logistic Regression. The results of this study showed that Logistic Regression has outperformed Naive Bayes with accuracy 82.26%. |
Other Details |
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Paper ID: IJSRDV7I60035 Published in: Volume : 7, Issue : 6 Publication Date: 01/09/2019 Page(s): 594-597 |
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