Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Georgiou, Konstantinos, Mittas, Nikolaos, Chatzigeorgiou, Alexandros, Angelis, Lefteris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
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
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
work_keys_str_mv AT georgioukonstantinos anempiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT mittasnikolaos anempiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT chatzigeorgioualexandros anempiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT angelislefteris anempiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT georgioukonstantinos empiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT mittasnikolaos empiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT chatzigeorgioualexandros empiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies
AT angelislefteris empiricalstudyofcovid19relatedpostsonstackoverflowtopicsandtechnologies