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The Swedish pandemic landscape on twitter: An exploratory study using statistical methods
Högskolan Väst, Institutionen för individ och samhälle, Avdelningen för psykologi, pedagogik och sociologi. Försvarshögskolan, Stockholm, (SWE). (LINA)ORCID-id: 0000-0003-0394-9724
Högskolan Väst, Institutionen för individ och samhälle, Avdelningen för psykologi, pedagogik och sociologi. (LINA)
Högskolan Väst, Institutionen för individ och samhälle, Avdelningen för psykologi, pedagogik och sociologi. (LINA)ORCID-id: 0000-0002-5259-0538
Sahlgrenska Academy, Gothenburg University, Gothenburg (SWE).ORCID-id: 0000-0002-2724-6372
2021 (engelsk)Inngår i: 26th International Command and Control Research and Technology Symposium (ICCRTS): Artificial Intelligence, Automation and Autonomy: C2 Implications, Opportunities and Challenges / [ed] Alberts, David, Washington, 2021, Vol. Topic 2, s. 1-7, artikkel-id 10Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

During the Covid-19 pandemic social media have become an important tool for spreading information from government agencies regarding restrictions. Government accounts and public health care organizations have used different social media platforms such as Twitter to communicate with the Swedish public. The Swedish public have interacted with the information, arguing for a stricter or a more relaxed approach to Covid-19 recommendations. This social network analysis aims at exploring statistical methods to investigate patterns made by twitter accounts commenting the Swedish Armed Forces field hospital activities and the national Covid-19 strategy during the Covid-19 pandemic. Data was collected using the twitter platform and the Ncapture add-on with Google Chrome. The interactions stored in the tweets and replies section (TRS) from 227 twitter accounts were collected and coded with the NVivo auto code function. Twitter usernames that occurred in less than 35 % of the 227 TRS were deleted. The 227 extracted TRS were treated as scale items and occurring twitter-names which interacted with the TRS as respondents n=761. Analysis of the factor structure with PCA and CFA indicated four factors: 1) Military policy, 2) Right wing politics, 3) Law enforcement, 4) Politics and strategy. Structural Equation Modelling revealed interrelationships between the factors. Thus, Military policy, Law enforcement and Politics and strategy had a direct effect on Right wing politics. Politics and strategy had a direct effect on Military policy and Law enforcement. This study revealed that PCA, CFA and SEM have the potential to discover the core of a thought collective. Despite the obvious dangers with misinformation and political extremism on social media, policymakers need to tackle misinformation and disinformation, protecting electoral processes and facilitating public discussion, built on the three fundamental democratic principles of equality, representation and participation.

sted, utgiver, år, opplag, sider
Washington, 2021. Vol. Topic 2, s. 1-7, artikkel-id 10
Serie
International Command and Control Research and Technology Symposium (ICCRTS) proceedings, ISSN 2577-1604
Emneord [en]
Social media, Covid-19, pandemic
HSV kategori
Forskningsprogram
Arbetsintegrerat lärande
Identifikatorer
URN: urn:nbn:se:hv:diva-17429OAI: oai:DiVA.org:hv-17429DiVA, id: diva2:1601702
Konferanse
26th International Command and Control Research and Technology Symposium (ICCRTS)
Forskningsfinansiär
Swedish Armed Forces
Merknad

ISBN 9780999724616

Tilgjengelig fra: 2021-10-10 Laget: 2021-10-10 Sist oppdatert: 2021-11-03bibliografisk kontrollert

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Schüler, MartinVega Matuszczyk, JosefaJohansson, Kriistina

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