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   <dc:title>Data Journalism Projects Based on User-Generated Content. How La Nacion Data Transforms Active Audience into Staff</dc:title>
   <dc:creator>Palomo-Torres, María Bella</dc:creator>
   <dc:creator>Teruel-Rodríguez, Laura</dc:creator>
   <dc:creator>Blanco-Castilla, Elena Pilar</dc:creator>
   <dc:subject>Sistemas de información - Análisis</dc:subject>
   <dcterms:abstract>This article aims to contribute to the debate on audience participation&#xd;
in the media from three points of view: (1) demonstrating&#xd;
how data journalism enables an effective participation by the&#xd;
public in news production, (2) establishing a typology of the&#xd;
forms of contribution, and (3) performing an in-depth study of La&#xd;
Naci on (Argentina), as an example of success in collaborative data&#xd;
projects carried out in Latin America. In order to achieve these&#xd;
objectives, firstly, all the Global Editors Network Data Journalism&#xd;
Awards were analysed with the purpose of detecting projects&#xd;
involving user-generated content. Secondly, La Naci on was&#xd;
studied from an ethnographic perspective, as it is the medium&#xd;
with the most prizes in which citizen participation was detected.&#xd;
The results show that collaboration between media and audience&#xd;
can make large-scale journalism projects a reality, and also that&#xd;
citizens in Argentina are recruited by LN Data specially to boost&#xd;
political accountability.</dcterms:abstract>
   <dcterms:dateAccepted>2025-01-27T09:54:26Z</dcterms:dateAccepted>
   <dcterms:available>2025-01-27T09:54:26Z</dcterms:available>
   <dcterms:created>2025-01-27T09:54:26Z</dcterms:created>
   <dcterms:issued>2019-06-13</dcterms:issued>
   <dc:type>journal article</dc:type>
   <dc:identifier>Bella Palomo, Laura Teruel &amp; Elena Blanco-Castilla (2019): Data Journalism Projects Based on User-Generated Content. How La Nacion Data Transforms Active Audience into Staff, Digital Journalism,</dc:identifier>
   <dc:identifier>https://hdl.handle.net/10630/37037</dc:identifier>
   <dc:identifier>10.1080/21670811.2019.1626257</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:rights>open access</dc:rights>
   <dc:publisher>Taylor &amp; Francis</dc:publisher>
</qdc:qualifieddc>
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