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Social media data analysis to predict mental state of users using machine learning techniques

BACKGROUND: Social media platforms such as Facebook, WhatsApp, and Instagram etc., are becoming very popular now not only for youth but for all walks of life. People are more often seen in busy in tweeting, chatting, or putting selfies. No one actually knows the mental state of a person in the onlin...

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Autores principales: Lokeshkumar, R., Mishra, Om Ashish, Kalra, Shivam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459879/
https://www.ncbi.nlm.nih.gov/pubmed/34667801
http://dx.doi.org/10.4103/jehp.jehp_446_20
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author Lokeshkumar, R.
Mishra, Om Ashish
Kalra, Shivam
author_facet Lokeshkumar, R.
Mishra, Om Ashish
Kalra, Shivam
author_sort Lokeshkumar, R.
collection PubMed
description BACKGROUND: Social media platforms such as Facebook, WhatsApp, and Instagram etc., are becoming very popular now not only for youth but for all walks of life. People are more often seen in busy in tweeting, chatting, or putting selfies. No one actually knows the mental state of a person in the online platform. In this article, we will be focusing on how social media is affecting issues such as road accident, murder, and suicide. The research is done by three parts. MATERIALS AND METHODS: Google Form analysis, machine learning used for prediction, and by sentimental analysis of what people think in twitter. All the datasets are based in India. From these datasets, the different machine learning algorithm is used to do the analysis. The project strives to bring the real-world solution in the matter of advancement. RESULTS: The static data analysis and dynamic data analysis shows the various sentimental analysis and predictions and the technique to predict different mental states. Thus we get clearly about the current world is getting into social issues. This research findings helps to bring social awareness among the current generation by understanding the sensitivity of the youths. CONCLUSION: Thus through this paper we get known clearly how the current world is getting into social issues like victim of murders or road accidents or committing suicide. The paper clearly helps us to understand the sensitivity of the youths. Therefore brings a social awareness among the current generation.
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spelling pubmed-84598792021-10-18 Social media data analysis to predict mental state of users using machine learning techniques Lokeshkumar, R. Mishra, Om Ashish Kalra, Shivam J Educ Health Promot Original Article BACKGROUND: Social media platforms such as Facebook, WhatsApp, and Instagram etc., are becoming very popular now not only for youth but for all walks of life. People are more often seen in busy in tweeting, chatting, or putting selfies. No one actually knows the mental state of a person in the online platform. In this article, we will be focusing on how social media is affecting issues such as road accident, murder, and suicide. The research is done by three parts. MATERIALS AND METHODS: Google Form analysis, machine learning used for prediction, and by sentimental analysis of what people think in twitter. All the datasets are based in India. From these datasets, the different machine learning algorithm is used to do the analysis. The project strives to bring the real-world solution in the matter of advancement. RESULTS: The static data analysis and dynamic data analysis shows the various sentimental analysis and predictions and the technique to predict different mental states. Thus we get clearly about the current world is getting into social issues. This research findings helps to bring social awareness among the current generation by understanding the sensitivity of the youths. CONCLUSION: Thus through this paper we get known clearly how the current world is getting into social issues like victim of murders or road accidents or committing suicide. The paper clearly helps us to understand the sensitivity of the youths. Therefore brings a social awareness among the current generation. Wolters Kluwer - Medknow 2021-08-31 /pmc/articles/PMC8459879/ /pubmed/34667801 http://dx.doi.org/10.4103/jehp.jehp_446_20 Text en Copyright: © 2021 Journal of Education and Health Promotion https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Lokeshkumar, R.
Mishra, Om Ashish
Kalra, Shivam
Social media data analysis to predict mental state of users using machine learning techniques
title Social media data analysis to predict mental state of users using machine learning techniques
title_full Social media data analysis to predict mental state of users using machine learning techniques
title_fullStr Social media data analysis to predict mental state of users using machine learning techniques
title_full_unstemmed Social media data analysis to predict mental state of users using machine learning techniques
title_short Social media data analysis to predict mental state of users using machine learning techniques
title_sort social media data analysis to predict mental state of users using machine learning techniques
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459879/
https://www.ncbi.nlm.nih.gov/pubmed/34667801
http://dx.doi.org/10.4103/jehp.jehp_446_20
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