Sentiment analysis in social networks of health institutions

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dc.contributor.authorÇonak, Özge
dc.contributor.authorÖnder, Emrah
dc.date.accessioned2025-03-09T18:06:24Z
dc.date.available2025-03-09T18:06:24Z
dc.date.issued2023
dc.departmentBeykent Üniversitesi
dc.description.abstractTwitter, a communication platform that creates a social impact; it conveys the messages of non-profit organizations to the masses and the emotions of the masses to non-profit organizations. This research; It aims to examine Twitter posts about health-related non-profit organizations, to determine the emotional states about these institutions on social media and to measure these feelings. Sentiment analysis about WHO, ILO, IOM, UNICEF, FAO, Red Cross, UNDP and UNHCR were carried out using the R program. The tweets used in sentiment analysis were collected by approval of Twitter API. During the study, a total of 310,341 tweets were collected in three periods, November 2019, May 2020 and October 2020. Tweets are classified according to 10 different emotions. One of the main findings of the study is that “positive”, “trust” and “anticipation” feelings are at the top of the tweets shared about these institutions under normal conditions and crisis conditions. Sentiment consistency was tested with Friedman test for each institution after emotional analysis was performed in all institutions (p
dc.identifier.doi10.17678/beuscitech.1222933
dc.identifier.endpage60
dc.identifier.issn2146-7706
dc.identifier.issue1
dc.identifier.startpage38
dc.identifier.urihttps://doi.org/10.17678/beuscitech.1222933
dc.identifier.urihttps://hdl.handle.net/20.500.12662/5040
dc.identifier.volume13
dc.language.isoen
dc.publisherBitlis Eren University
dc.relation.ispartofBitlis Eren University Journal of Science and Technology
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250309
dc.subjectHealth
dc.subjectSentiment Analysis
dc.subjectText Mining
dc.subjectNonprofit Organization
dc.subjectTwitter
dc.subjectHealth
dc.subjectSentiment Analysis
dc.subjectText Mining
dc.subjectNonprofit Organization
dc.subjectTwitter.
dc.titleSentiment analysis in social networks of health institutions
dc.typeArticle

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