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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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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. |
format | Online Article Text |
id | pubmed-8061158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
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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