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An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies()
The COVID-19 outbreak, also known as the coronavirus pandemic, has left its mark on every aspect of our lives and at the time of this writing is still an ongoing battle. Beyond the immediate global-wide health response, the pandemic has triggered a significant number of IT initiatives to track, visu...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8443319/ https://www.ncbi.nlm.nih.gov/pubmed/34545258 http://dx.doi.org/10.1016/j.jss.2021.111089 |
_version_ | 1783753161884827648 |
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author | Georgiou, Konstantinos Mittas, Nikolaos Chatzigeorgiou, Alexandros Angelis, Lefteris |
author_facet | Georgiou, Konstantinos Mittas, Nikolaos Chatzigeorgiou, Alexandros Angelis, Lefteris |
author_sort | Georgiou, Konstantinos |
collection | PubMed |
description | The COVID-19 outbreak, also known as the coronavirus pandemic, has left its mark on every aspect of our lives and at the time of this writing is still an ongoing battle. Beyond the immediate global-wide health response, the pandemic has triggered a significant number of IT initiatives to track, visualize, analyze and potentially mitigate the phenomenon. For individuals or organizations interested in developing COVID-19 related software, knowledge-sharing communities such as Stack Overflow proved to be an effective source of information for tackling commonly encountered problems. As an additional contribution to the investigation of this unprecedented health crisis and to assess how fast and how well the community of developers has responded, we performed a study on COVID-19 related posts in Stack Overflow. In particular, we profiled relevant questions based on key post features and their evolution, identified the most prominent technologies adopted for developing COVID-19 software and their interrelations and focused on the most persevering problems faced by developers. For the analysis of posts we employed descriptive statistics, Association Rule Graphs, Survival Analysis and Latent Dirichlet Allocation. The results reveal that the response of the developers’ community to the pandemic was immediate and that the interest of developers on COVID-19 related challenges was sustained after its initial peak. In terms of the problems addressed, the results show a clear focus on COVID-19 data collection, analysis and visualization from/to the web, in line with the general needs for monitoring the pandemic. |
format | Online Article Text |
id | pubmed-8443319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84433192021-09-16 An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() Georgiou, Konstantinos Mittas, Nikolaos Chatzigeorgiou, Alexandros Angelis, Lefteris J Syst Softw Article The COVID-19 outbreak, also known as the coronavirus pandemic, has left its mark on every aspect of our lives and at the time of this writing is still an ongoing battle. Beyond the immediate global-wide health response, the pandemic has triggered a significant number of IT initiatives to track, visualize, analyze and potentially mitigate the phenomenon. For individuals or organizations interested in developing COVID-19 related software, knowledge-sharing communities such as Stack Overflow proved to be an effective source of information for tackling commonly encountered problems. As an additional contribution to the investigation of this unprecedented health crisis and to assess how fast and how well the community of developers has responded, we performed a study on COVID-19 related posts in Stack Overflow. In particular, we profiled relevant questions based on key post features and their evolution, identified the most prominent technologies adopted for developing COVID-19 software and their interrelations and focused on the most persevering problems faced by developers. For the analysis of posts we employed descriptive statistics, Association Rule Graphs, Survival Analysis and Latent Dirichlet Allocation. The results reveal that the response of the developers’ community to the pandemic was immediate and that the interest of developers on COVID-19 related challenges was sustained after its initial peak. In terms of the problems addressed, the results show a clear focus on COVID-19 data collection, analysis and visualization from/to the web, in line with the general needs for monitoring the pandemic. Elsevier Inc. 2021-12 2021-09-16 /pmc/articles/PMC8443319/ /pubmed/34545258 http://dx.doi.org/10.1016/j.jss.2021.111089 Text en © 2021 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Georgiou, Konstantinos Mittas, Nikolaos Chatzigeorgiou, Alexandros Angelis, Lefteris An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title | An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title_full | An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title_fullStr | An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title_full_unstemmed | An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title_short | An empirical study of COVID-19 related posts on Stack Overflow: Topics and technologies() |
title_sort | empirical study of covid-19 related posts on stack overflow: topics and technologies() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8443319/ https://www.ncbi.nlm.nih.gov/pubmed/34545258 http://dx.doi.org/10.1016/j.jss.2021.111089 |
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