{"title":"Fighting COVID-19 with data: An analysis of data journalism projects submitted to Sigma Awards 2021","authors":"Liis Auväärt","doi":"10.51480/1899-5101.15.3(32).3","DOIUrl":null,"url":null,"abstract":"Abstract: The COVID-19 health crisis has been heavily reported on an international scale for several years. This has pushed news journalism in a datafied direction: reporters have learnt how to analyse and visualise the statistical effects of COVID-19 on various sectors of society. As a result, in 2021, the international Sigma Awards competition for data journalism highlighted coverage of the pandemic. Using content analysis with qualitative elements, this paper analyses the shortlisted works covering COVID-19 from the competition (n=73). It focuses on the data references made by the teams – sources, type of both reference and data used – showing statistics from official institutions to be the most used type of data. It also lists the main problems journalists had to face while working on their projects. Most often these problems fell into two categories: specific characteristics of the project, mostly ‘time consuming’, and issues with data.","PeriodicalId":40610,"journal":{"name":"Central European Journal of Communication","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central European Journal of Communication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51480/1899-5101.15.3(32).3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract: The COVID-19 health crisis has been heavily reported on an international scale for several years. This has pushed news journalism in a datafied direction: reporters have learnt how to analyse and visualise the statistical effects of COVID-19 on various sectors of society. As a result, in 2021, the international Sigma Awards competition for data journalism highlighted coverage of the pandemic. Using content analysis with qualitative elements, this paper analyses the shortlisted works covering COVID-19 from the competition (n=73). It focuses on the data references made by the teams – sources, type of both reference and data used – showing statistics from official institutions to be the most used type of data. It also lists the main problems journalists had to face while working on their projects. Most often these problems fell into two categories: specific characteristics of the project, mostly ‘time consuming’, and issues with data.
期刊介绍：
Central European Journal of Communication provides an international forum for empirical, critical and interpretative, quantitative and qualitative research examining the role of communication in Central Europe and beyond. The journal welcomes high quality research and analysis from diverse theoretical and methodological approaches, as well as reviews of publications and publishes notes on a wide range of literature on media and communication studies. Submission of original articles is open to all researchers interested in communication and media.
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