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2023-07-27Zeitschriftenartikel
Investigating the aftermath of the Türkiye 2023 earthquake: exploring post-disaster uncertainty among Syrian migrants using social network analysis with public health approach
dc.contributor.authorAktuna, Gamze
dc.contributor.authorBahar-Özvarış, Şevkat
dc.date.accessioned2026-01-14T11:59:19Z
dc.date.available2026-01-14T11:59:19Z
dc.date.issued2023-07-27none
dc.identifier.other10.3389/fpubh.2023.1204589
dc.identifier.urihttp://edoc.rki.de/176904/13124
dc.description.abstractObjectives: On February 6th, 2023, a doublet earthquake struck Türkiye, impacting more than 15 million people including migrants, and resulting in over 50,000 deaths. The Syrian migrants experience multiple uncertainties in their daily lives which are further compounded by multifaceted challenges of the post-disaster environment. Social media was used intensively and with impunity in this environment and thereby provides a window into the explicit and implicit dynamics of daily life after a disaster. We aimed to explore how a post-disaster environment potentially generates new uncertainties or exacerbating pre-existing ones for migrants through social media analysis with an indirect perspective, in the context of 2023-Earthquake in Türkiye and Syrian migrants. Methods: Social network analysis was used to analyze Twitter-data with the hashtags ‘Syrian’ and ‘earthquake’ during a 10-day period beginning on March 22nd, 2023. We calculated network metrics, including degree-values and betweenness-centrality and clustered the network to understand groups. We analyzed a combination of 27 tweets with summative content analysis using a text analysis tool, to identify the most frequently used words. We identified the main points of each tweet and assessed these as possible contributors to post-disaster uncertainty among migrants by using inductive reasoning. Results: There were 1918 Twitter users, 274 tweets, 124 replies and 1726 mentions. Discussions about Syrian migrants and earthquakes were established across various groups (ngroups(edges > 15) = 16). Certain users had a greater influence on the overall network. The nine most frequently used words were included under uncertainty-related category (nmost_frequently_used_words = 20); ‘aid, vote, house, citizen, Afghan, illegal, children, border, and leave’. Nine main points were identified as possible post-disaster uncertainties among migrants. Conclusion: The post-disaster environment has the potential to exacerbate existing uncertainties, such as being an undocumented migrant, concerns about deportation and housing, being or having a child, inequality of rights between being a citizen and non-citizen, being in minority within minority, political climate of the host nation and access to education or to generate new ones such equitable distribution of aid, which can lead to poor health outcomes. Recognizing the possible post-disaster uncertainties among migrants and addressing probable underlying factors might help to build more resilient and healthy communities.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subjectuncertaintyeng
dc.subjectmigrants and refugeeseng
dc.subjectearthquakeeng
dc.subjectdisastereng
dc.subjectsocial network analysiseng
dc.subjectcontent analysiseng
dc.subjectTurkeyeng
dc.subjectSyrianeng
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleInvestigating the aftermath of the Türkiye 2023 earthquake: exploring post-disaster uncertainty among Syrian migrants using social network analysis with public health approachnone
dc.typearticle
dc.identifier.urnurn:nbn:de:0257-176904/13124-1
dc.type.versionpublishedVersionnone
local.edoc.container-titleFrontiers in Public Healthnone
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameFrontiers Media SA.none
local.edoc.container-reportyear2023none
local.edoc.container-firstpage01none
local.edoc.container-lastpage13none
dc.description.versionPeer Reviewednone

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