24 Mayıs 2023 Veri seti Açık Erişim

Yersel Burçin; Kalkan Başak; Özer Çelen Arzu; Korul Ulukan Aysel

Dublin Core

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Yersel Burçin</dc:creator>
  <dc:creator>Kalkan Başak</dc:creator>
  <dc:creator>Özer Çelen Arzu</dc:creator>
  <dc:creator>Korul Ulukan Aysel</dc:creator>
  <dc:date>2023-05-24</dc:date>
  <dc:description>The purpose of this research is to examine the activities of the World Health Organization, which stands out with its international studies in the pandemic, and health ministries in countries with the highest number of cases are seen, from the perspective of digital communication, during the period when the vaccination against the Covid-19 epidemic,which started to show its effect all over the world since March 2019. In the epidemic period, digital platforms have gained importance and been used more than ever by minimizing physical interaction between people and creating communication environments independent of time and place. Governments have also turned to digital platforms that offer instant, unmediated interaction opportunities and have realized the flow of information through these platforms in delivering their policies to the public. In this context, the shares of the World Health Organization and the first two countries with the highest number of cases due to the pandemic, the United States and India's ministries of health, on Twitter, which is a social sharing platform, will be comparatively analyzed using text mining methods. Text mining is an artificial intelligence (AI) technology that uses natural language processing (NLP) to make unstructured text in documents and databases suitable for analysis, in other words, into structured data. RStudio programming language, which is a free and open source software program for data science, will be used in data collection. In the study, firstly, the most frequently used words in the posts will be found, and then the emotions in the statements will be examined by making an analysis of the posts. Sntiment analysis is the process of determining the emotional tone behind a series of words used to ensure understanding of attitudes, ideas and emotions expressed verbally on digital platforms. With the findings obtained, the language used in digital communication activities of the World Health Organization and the ministries of health, which is a public institution, will be systematically defined and analyzed comparatively. </dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/252428</dc:identifier>
  <dc:identifier>10.48623/aperta.252428</dc:identifier>
  <dc:identifier>oai:aperta.ulakbim.gov.tr:252428</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
  <dc:subject>Covid-19 Pandemic, Digital Communication, Text Mining, Sentiment Analysis</dc:subject>
  <dc:title>Radio listening trends research data</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
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