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Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification

In present modern era, the outbreak of COVID-19 pandemic has created informational crisis. The public sentiments collected from different reflexions (hashtags, comments, tweets, posts of twitter) are measured accordingly, ensuring different policy decisions and messaging are incorporated. The implem...

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Detalles Bibliográficos
Autores principales: Ramya, B. N., Shetty, Shyleshwari M., Amaresh, A. M., Rakshitha, R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8061158/
https://www.ncbi.nlm.nih.gov/pubmed/33907735
http://dx.doi.org/10.1007/s42979-021-00625-5
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author Ramya, B. N.
Shetty, Shyleshwari M.
Amaresh, A. M.
Rakshitha, R.
author_facet Ramya, B. N.
Shetty, Shyleshwari M.
Amaresh, A. M.
Rakshitha, R.
author_sort Ramya, B. N.
collection PubMed
description In present modern era, the outbreak of COVID-19 pandemic has created informational crisis. The public sentiments collected from different reflexions (hashtags, comments, tweets, posts of twitter) are measured accordingly, ensuring different policy decisions and messaging are incorporated. The implementation demonstrates intuition in to the advancement of fear sentiment eventually as COVID-19 approaches maximum levels in the world, by making use of detailed textual analysis with the help of required text data visualization. In addition, technical outline of machine learning stratification approaches are provided in the frame of text analytics, and comparing their efficiency in stratifying coronavirus tweets of different lengths. Using Naïve Bayes method, 91% accuracy is achieved for short tweets and using logistic regression classification method, 74% accuracy is achieved for short tweets.
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spelling pubmed-80611582021-04-23 Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification Ramya, B. N. Shetty, Shyleshwari M. Amaresh, A. M. Rakshitha, R. SN Comput Sci Original Research In present modern era, the outbreak of COVID-19 pandemic has created informational crisis. The public sentiments collected from different reflexions (hashtags, comments, tweets, posts of twitter) are measured accordingly, ensuring different policy decisions and messaging are incorporated. The implementation demonstrates intuition in to the advancement of fear sentiment eventually as COVID-19 approaches maximum levels in the world, by making use of detailed textual analysis with the help of required text data visualization. In addition, technical outline of machine learning stratification approaches are provided in the frame of text analytics, and comparing their efficiency in stratifying coronavirus tweets of different lengths. Using Naïve Bayes method, 91% accuracy is achieved for short tweets and using logistic regression classification method, 74% accuracy is achieved for short tweets. Springer Singapore 2021-04-22 2021 /pmc/articles/PMC8061158/ /pubmed/33907735 http://dx.doi.org/10.1007/s42979-021-00625-5 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Research
Ramya, B. N.
Shetty, Shyleshwari M.
Amaresh, A. M.
Rakshitha, R.
Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title_full Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title_fullStr Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title_full_unstemmed Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title_short Smart Simon Bot with Public Sentiment Analysis for Novel Covid-19 Tweets Stratification
title_sort smart simon bot with public sentiment analysis for novel covid-19 tweets stratification
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8061158/
https://www.ncbi.nlm.nih.gov/pubmed/33907735
http://dx.doi.org/10.1007/s42979-021-00625-5
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