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Dataset Open Access

A dataset of media realeases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research

Andrzej Jarynowski

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  <identifier identifierType="DOI">10.5281/zenodo.3985568</identifier>
      <creatorName>Andrzej Jarynowski</creatorName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="">0000-0003-0949-6674</nameIdentifier>
      <affiliation>Interdisciplinary Research Institute in Wrocław</affiliation>
    <title>A dataset of media realeases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research</title>
    <subject>media analysis</subject>
    <subject>risk perception</subject>
    <date dateType="Issued">2020-08-14</date>
  <resourceType resourceTypeGeneral="Dataset"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3985567</relatedIdentifier>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. IWith this dataset&amp;nbsp;we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07&amp;nbsp;and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach.&lt;/p&gt;

&lt;p&gt;- manually coded 1,449 articles&amp;nbsp;/ Facebook posts from Lower Silesia ( and 111 texts from outside this region;&lt;/p&gt;

&lt;p&gt;-extracted 57,306 representative articles (;nbsp;in Polish using tool in language Polish&amp;nbsp;and topic &amp;quot;Coronavirus&amp;quot; in article body;&lt;/p&gt;

&lt;p&gt;- extracted 1,015,199 ( and and Tweets from #Koronawirus in language Polish in Twitter.&lt;/p&gt;

&lt;p&gt;- collected 1,574 videos ( and youtube_movie.csv) with&amp;nbsp;keyword: Koronawirus&amp;nbsp;on YouTube and 247,575 comments on them;&lt;/p&gt;

&lt;p&gt;- We supplemented the media observations with an analysis of 244 social empirical studies on COVID-19 in Poland (empirical_studies.csv).&lt;/p&gt;

&lt;p&gt;Reports and analyzes and coding books&amp;nbsp;can be found in Polish at:&amp;nbsp;&lt;a href=""&gt;;/a&gt;&lt;/p&gt;</description>
    <description descriptionType="Other">{"references": ["Jarynowski A, W\u00f3jta-Kempa M, Belik V. TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET, Polish Epidemiological Review", "Jarynowski A, W\u00f3jta-Kempa  M, P\u0142atek D, Krzowski \u0141, Belik V. Spatial Diversity of COVID-19 Cases in Poland Explained by Mobility Patterns - Preliminary Results 2020;"]}</description>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/831644/">831644</awardNumber>
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