Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33370
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dc.contributor.authorMittal, Ruchien_UK
dc.contributor.authorAhmed, Wasimen_UK
dc.contributor.authorMittal, Amiten_UK
dc.contributor.authorAggarwal, Ishanen_UK
dc.date.accessioned2021-10-06T00:00:39Z-
dc.date.available2021-10-06T00:00:39Z-
dc.date.issued2021-09-22en_UK
dc.identifier.urihttp://hdl.handle.net/1893/33370-
dc.description.abstractPurpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.en_UK
dc.language.isoenen_UK
dc.publisherEmeralden_UK
dc.relationMittal R, Ahmed W, Mittal A & Aggarwal I (2021) Twitter users’ coping behaviors during the COVID-19 lockdown: an analysis of tweets using mixed methods. Information Discovery and Delivery, 49 (3), pp. 193-202. https://doi.org/10.1108/idd-08-2020-0102en_UK
dc.rightsPublisher policy allows this work to be made available in this repository. Published in Information Discovery and Delivery by Emerald. Mittal, R., Ahmed, W., Mittal, A. and Aggarwal, I. (2021), "Twitter users’ coping behaviors during the COVID-19 lockdown: an analysis of tweets using mixed methods", Information Discovery and Delivery, Vol. 49 No. 3, pp. 193-202. The original publication is available at: https://doi.org/10.1108/IDD-08-2020-0102 Creative Commons Attribution Non-commercial International Licence 4.0 (CC BY-NC 4.0). To reuse the AAM for commercial purposes, permission should be sought by contacting permissions@emeraldinsight.com.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en_UK
dc.subjectCOVID-19en_UK
dc.subjectPandemicen_UK
dc.subjectCopingen_UK
dc.subjectTwitteren_UK
dc.subjectLockdownen_UK
dc.subjectMixed-methodsen_UK
dc.titleTwitter users’ coping behaviors during the COVID-19 lockdown: an analysis of tweets using mixed methodsen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1108/idd-08-2020-0102en_UK
dc.citation.jtitleInformation Discovery and Deliveryen_UK
dc.citation.issn2398-6247en_UK
dc.citation.issn2398-6247en_UK
dc.citation.volume49en_UK
dc.citation.issue3en_UK
dc.citation.spage193en_UK
dc.citation.epage202en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderNewcastle Universityen_UK
dc.author.emailwasim.ahmed@stir.ac.uken_UK
dc.citation.date15/05/2021en_UK
dc.contributor.affiliationChitkara Universityen_UK
dc.contributor.affiliationNewcastle Universityen_UK
dc.contributor.affiliationChitkara Universityen_UK
dc.contributor.affiliationEricsson India Global Servicesen_UK
dc.identifier.isiWOS:000652467700001en_UK
dc.identifier.scopusid2-s2.0-85106342764en_UK
dc.identifier.wtid1759474en_UK
dc.contributor.orcid0000-0001-8923-1865en_UK
dc.date.accepted2021-03-02en_UK
dcterms.dateAccepted2021-03-02en_UK
dc.date.filedepositdate2021-09-29en_UK
dc.subject.tagCOVID-19en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorMittal, Ruchi|en_UK
local.rioxx.authorAhmed, Wasim|0000-0001-8923-1865en_UK
local.rioxx.authorMittal, Amit|en_UK
local.rioxx.authorAggarwal, Ishan|en_UK
local.rioxx.projectProject ID unknown|Newcastle University|http://dx.doi.org/10.13039/501100000774en_UK
local.rioxx.freetoreaddate2021-10-05en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nc/4.0/|2021-10-05|en_UK
local.rioxx.filenameIDDAuthorAcceptedV.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source2398-6247en_UK
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