Depression prognosis using natural language processing and machine learning from social media status
نویسندگان
چکیده
<p><span>Depression is an acute problem throughout the world. Due to worst and prolong depression many people dies in every year. The that most of are not concern fact they suffering from depression. In this research, our aim was find out whether individual depressed or by analyzing social media status. Therefore, we focused on real data. Our dataset consists 2000 sentences, which collected different platforms Facebook, Twitter, Instagram. Then, have performed five data pre-processing approaches for natural language processing (NLP) such as tokenization, removal stop words, removing empty string, punctuations, stemming lemmatization. For selected model, considered processed input. Finally, applied six machine learning (ML) classifiers multinomial Naive Bayes (NB), logistic regression, liner support vector classifier, random forest, K-nearest neighbour, decision tree achieve better accuracy over dataset. Among algorithms, NB regression well obtained 98% accuracy.</span></p>
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ژورنال
عنوان ژورنال: International Journal of Electrical and Computer Engineering
سال: 2022
ISSN: ['2088-8708']
DOI: https://doi.org/10.11591/ijece.v12i3.pp2847-2855