Patterns in Award Winning Data Storytelling: Story Types, Enabling Tools and Competences

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Title: Patterns in Award Winning Data Storytelling: Story Types, Enabling Tools and Competences
Authors: Ojo, AdegboyegaHeravi, Bahareh R.
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Date: 3-Jul-2018
Online since: 2020-07-17T16:13:54Z
Abstract: Data storytelling is rapidly gaining prominence as a characteristic activity of digital journalism with significant adoption by small and large media houses. While a handful of previous studies have examined what characterises aspects of data storytelling like narratives and visualisation or analysis based on single cases, we are yet to see a systematic effort to harness these available resources to gain better insight into what characterises good data stories and how these are created. This study analysed 44 cases of outstanding data storytelling practices comprising winning entries of the Global Editors Network’s Data Journalism Award from 2013 to 2016 to bridge this knowledge gap. Based on a conceptual model we developed, we uniformly characterised each of the 44 cases and then proceeded to determine types of these stories and the nature of technologies employed in creating them. Our findings refine the traditional typology of data stories from the journalistic perspective and also identify core technologies and tools that appear central to good data journalism practice. We also discuss our findings in relations to the recently published 2017 winning entries. Our results have significant implications for the required competencies for data journalists in contemporary and future newsrooms.
Type of material: Journal Article
Publisher: Taylor & Francis
Journal: Digital Journalism
Volume: 6
Issue: 6
Start page: 693
End page: 718
Copyright (published version): 2017 Taylor & Francis
Keywords: CommunicationData-driven journalismData journalism skillsData journalism toolsData storyData storytelling typesGlobal editor networkBig dataComputational journalismAnalytics
DOI: 10.1080/21670811.2017.1403291
Language: en
Status of Item: Peer reviewed
ISSN: 2167-0811
Appears in Collections:Information and Communication Studies Research Collection
Insight Research Collection

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