Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Depression is known to be the biggest contributor to global illness, and a significant cause of suicide. In this paper, our study's main purpose is to review posts from Reddit users to identify any factors that may expose the depression attitudes of local online users. NLP is a field in machine learning with the ability of a computer to understand, analyze, manipulate, and potentially generate human language. Here we used sentiment analysis. Instead of constructing all resources from scratch, NLTK does have all that NLP tasks. The proposed framework is developed by using Logistic Regression, Support Vector Machine, Random Forest, Adaptive Boosting and Multilayer Perceptron classifier. Logistic Regression (LR) is a linear classification approach used to estimate the probability occurrence of binary response based on one or more predictors and features. We used the clustering techniques k-mean to Cluster user data, and provide the user with accuracy stress levels. Using clustering of k-means, we developed four
Keywords:
Natural language processing, Reddit social media, Stress level prediction, Artificial intelligence, Anxiety.
Cite Article:
"Anxiety And depression Posts In Reddit Social Media ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 9, page no.1 - 6, September-2020, Available :http://www.ijrti.org/papers/IJRTI2009001.pdf
Downloads:
000204828
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator