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Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19
To effectively design policies and implement measures for addressing problems faced by people during these difficult times of pandemic, it is critical to have a clear vision of the problems people are freely talking about. One of the ways is to analyze social media feeds e.g., tweets, which has beco...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035975/ https://www.ncbi.nlm.nih.gov/pubmed/37363804 http://dx.doi.org/10.1007/s42001-023-00201-2 |
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author | Sukhavasi, Narendranath Misra, Janardan Kaulgud, Vikrant Podder, Sanjay |
author_facet | Sukhavasi, Narendranath Misra, Janardan Kaulgud, Vikrant Podder, Sanjay |
author_sort | Sukhavasi, Narendranath |
collection | PubMed |
description | To effectively design policies and implement measures for addressing problems faced by people during these difficult times of pandemic, it is critical to have a clear vision of the problems people are freely talking about. One of the ways is to analyze social media feeds e.g., tweets, which has become one of the primary ways people express their views on various socioeconomic issues and on-ground effectiveness of measures adopted to address these issues. In this work, we attempt to uncover various socioeconomic issues, which are giving rise to negative and positive sentiments and their trends across geographies over a course of one year of the pandemic. We also try identifying similarities and differences in opinions as they vary across gender as the time passes through the crisis. Many previous works have analyzed sentiments in context of vaccines, fatalities, and lockdowns; however, socioeconomic issues did not receive full attention. We found that sentiments of people with respect to economy are negative across geographies during starting of pandemic. Thereafter, gradually sentiments lift towards positive direction reflecting a sense of improvement in situation. Females appeared to have slightly different concerns and hopes in comparison to males and especially across globe people expressed positive sentiments during new year time. Finally, this work, together with many other similar works on social media analysis gives ground for wide scale adoption of geo-temporal sentiments trend analysis of social media as a tool for uncovering key concerns and effectiveness of measures. |
format | Online Article Text |
id | pubmed-10035975 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-100359752023-03-24 Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 Sukhavasi, Narendranath Misra, Janardan Kaulgud, Vikrant Podder, Sanjay J Comput Soc Sci Research Article To effectively design policies and implement measures for addressing problems faced by people during these difficult times of pandemic, it is critical to have a clear vision of the problems people are freely talking about. One of the ways is to analyze social media feeds e.g., tweets, which has become one of the primary ways people express their views on various socioeconomic issues and on-ground effectiveness of measures adopted to address these issues. In this work, we attempt to uncover various socioeconomic issues, which are giving rise to negative and positive sentiments and their trends across geographies over a course of one year of the pandemic. We also try identifying similarities and differences in opinions as they vary across gender as the time passes through the crisis. Many previous works have analyzed sentiments in context of vaccines, fatalities, and lockdowns; however, socioeconomic issues did not receive full attention. We found that sentiments of people with respect to economy are negative across geographies during starting of pandemic. Thereafter, gradually sentiments lift towards positive direction reflecting a sense of improvement in situation. Females appeared to have slightly different concerns and hopes in comparison to males and especially across globe people expressed positive sentiments during new year time. Finally, this work, together with many other similar works on social media analysis gives ground for wide scale adoption of geo-temporal sentiments trend analysis of social media as a tool for uncovering key concerns and effectiveness of measures. Springer Nature Singapore 2023-03-23 /pmc/articles/PMC10035975/ /pubmed/37363804 http://dx.doi.org/10.1007/s42001-023-00201-2 Text en © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. 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 | Research Article Sukhavasi, Narendranath Misra, Janardan Kaulgud, Vikrant Podder, Sanjay Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title | Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title_full | Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title_fullStr | Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title_full_unstemmed | Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title_short | Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19 |
title_sort | geo-sentiment trends analysis of tweets in context of economy and employment during covid-19 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035975/ https://www.ncbi.nlm.nih.gov/pubmed/37363804 http://dx.doi.org/10.1007/s42001-023-00201-2 |
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