Ojo, Adegboyega and Heravi, Bahareh
(2018)
Patterns in Award Winning Data Storytelling.
Digital Journalism, 6 (6).
pp. 693-718.
ISSN 2167-0811
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.
Item Type: |
Article
|
Keywords: |
data-driven journalism; data journalism skills; data journalism tools; data story;
data storytelling types; Global Editor Network; |
Academic Unit: |
Faculty of Social Sciences > School of Business |
Item ID: |
13185 |
Identification Number: |
https://doi.org/10.1080/21670811.2017.1403291 |
Depositing User: |
Adegboyega Ojo
|
Date Deposited: |
14 Aug 2020 15:09 |
Journal or Publication Title: |
Digital Journalism |
Publisher: |
Taylor & Francis (Routledge) |
Refereed: |
Yes |
URI: |
|
Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
Repository Staff Only(login required)
|
Item control page |
Downloads per month over past year
Origin of downloads