News Production Workflows in Data- driven, Algorithmic Journalism: A Systematic Literature Review

MEDIA & DESIGN
News Production Workflows in Data-
driven, Algorithmic Journalism
A Systematic Literature Review
Julian Ausserhofer1,2
,
@julauss
Robert Gutounig1
&
@sextus_empirico
Michael Oppermann2
@oppermann_m
1: FH Joanneum University of Applied Sciences Graz
2: University of Vienna
Dubrovnik Media Days, 31.10.15
#DuMD2015 & #DUMediaDays

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*Tool evaluation partners
*
*
*
Supported by:

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Research Interest

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#DuMD2015 & #DUMediaDays @julauss, @sextus_empirico & @oppermann_m 4
"experimental use of algorithms, data and social
science methods" in journalism (Gynnild, 2014, p. 715)

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@julauss, @sextus_empirico & @oppermann_m 5
(Cox, 2000)
http://www.computerhistory.org/revolution/early-computer-companies/5/102/445
(Meyer, 1973)
1952
Computational methods in journalism

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(Garrison, 1996)

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The datafication of journalism
"datafication" of society
(Mayer-Schönberger & Cukier, 2013)
"increased focus on measurement, outcomes
assessment" (Anderson, 2015, p. 363)
"journalism's quantitative turn" (Coddington, 2015)
… has also affected the "infrastructures of
journalism" (Russ-Mohl, 2006, p.199)

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Research literature on data journalism
"internalist tendencies at [... the] early stage of
academic research" (Anderson, 2013, p. 1007)
↓
"an explosion in data journalism-oriented
scholarship" (Fink & Anderson, 2015, p. 476)*
"rapidly growing body" of scientific studies
(Lewis, 2015, p. 322)*
*cited via (Loosen, Reimer & Schmidt, 2015, p. 2)

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In what way have journalistic workflows and
routines changed due to the broad introduction of
data in the newsroom?
How has this impacted journalistic norms and
ethics, and the skill requirements for journalists?
Research questions

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#DuMD2015 & #DUMediaDays @julauss, @sextus_empirico & @oppermann_m 11
Systematic literature review

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"to develop insights, critical reflections, future
research paths and research questions"
(Massaro, Dumay & Guthrie, forthcoming)
It adopts "a replicable, scientific and transparent
process [...] that aims to minimize bias [...]"
(Tranfield, Denyer & Smart, 2003)
Why a systematic literature review?

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Undertaking a systematic literature review
13
Adapted from Massaro et al. (forthcoming)
Own visualization
@julauss, @sextus_empirico & @oppermann_m#DuMD2015 & #DUMediaDays
Writing a literature review protocol
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
Coding dataDefining the
questions that
the literature
review should
answer

MEDIA & DESIGN
14
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
Defining the
questions that
the literature
review should
answer
In what way have journalistic workflows and
routines changed due to the broad introduction of
data in the newsroom?
How has this impacted journalistic norms and
ethics, and the skill requirements for journalists?

MEDIA & DESIGN
15
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Defining the
questions that
the literature
review should
answer
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
● Empirical research on DDJ
● Social science focus, but open to other disciplines
● Published after 1995
Included
Journal articles
Book sections
Conference papers
Reports (from industry and
research projects)
PhD theses
Not included
Bachelor's and Master's theses
Press reports
Blog posts

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16
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Defining the
questions that
the literature
review should
answer
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
● Preliminary search with “data-driven journalism”
● Extracting related terms from the keyword
section of research papers

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17
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Defining the
questions that
the literature
review should
answer
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
Search terms
algorithmic journalism
computational journalism
computer-assisted reporting
data journalism
data-driven journalism
data-driven reporting
database journalism
datajournalism
datenjournalismus
quantitative journalism
No search terms
accountability journalism
crowdsourced journalism
dataviz
datavis
ddj
drone journalism
investigative journalism
online journalism
open journalism

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18
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Defining the
questions that
the literature
review should
answer
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
Scientific Databases
ACM Digital Sowiport
EBSCO Springer
IEEE SpringerLink
JSTOR Taylor & Francis Online
ProQuest Web of Science
Science Direct Wiley
Scopus Google Scholar
Sociological Abstracts

MEDIA & DESIGN
19
Developing
insights and
critique
through
analyzing the
dataset
Developing
future research
paths and
questions
Coding data
Defining the
questions that
the literature
review should
answer
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
772 search results
↓
Assessment of title, abstract & keywords
- by two independently working researchers
(Thomas et al., 2004)
↓
33 research publications

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20
Determining
the type of
studies and
carrying out a
comprehensive
literature
search
Defining the
questions that
the literature
review should
answer
Developing
future research
paths and
questions
Developing
insights and
critique
through
analyzing the
dataset
Coding data
qualitative coding
computational analysis

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Literature Corpus

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23
Research literature on workflows in DDJ
Development of literature over time
n=33

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24@julauss, @sextus_empirico & @oppermann_m#DuMD2015 & #DUMediaDays
Publication type
Parasie &
Dagiral,
2013
Lewis &
Usher, 2013
Diakopolus,
2015
Karlsen &
Stavelin,
2014
n=33
node size = number of citations in Google Scholar

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Publication year of referenced papers
1787-2015
n=1151
Constitution of the
United States

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Publication year of referenced papers
1999-2015
n=1004
2013: 176 cited papers

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Most-cited references

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edges = 165
corpus publications, n=33
references, n = 70
size = nr. of citations from the corpus
Corpus and most-cited references
The Journalist as Programmer
Precision Journalism
Accountability through Algorithm

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Nr. of studies
Survey 3
In-depth interviews 22
(Particpant) observation 4
Method(s) of data collection

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Geographical scope
Nr. of studies Nr. of studies
United States 9 Multinational (>4) 2
United Kingdom 9 Norway 1
Germany 4 Netherlands 1
Sweden 2 Argentina 1
Switzerland 2 Austria 1
Finland 2 Belgium 1

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Qualitative analysis -
News Production Workflow

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News production workflow
Collecting
Collecting digitalized information from
● publicly available data sets
● requested data
● own research or data collected through crowdsourcing
● automated research (scraping)
● leaked data
(17; Loosen, 2015)

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Type of data source
● government or public bureau
● private corporation
● other organizations like NGOs, research institutes
(28, Loosen, 2015)
Collecting

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Access to information
in Norway and USA generally considered good (due to freedom of
information legislation)
Barriers to easy data access
● fees
● lacking competencies for exporting data at public offices
● the form data is often delivered (e.g. as PDF)
● lack of legal legal resources to get access to data that is denied
to journalists in the first place
(6; 14)
Collecting

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Selecting data
Because data journalists don’t have much time in the newsroom,
they prefer easy-accessible data, e.g. datasets from public bodies.
They are very cautious when it comes to work with data from
companies or private sources.
(14)
Collecting

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Methods
● Journalists use statistical programs (e.g. MySQL, Excel, Access,
SPSS, Google Docs, Maps, Google Refine, Google Fusion Tables
etc.)
● Statistical methods and packages including cluster, network &
regression analysis
--> Journalists are quite cautious with it, since they consider this
outside of their field of expertise.
(6, 14)
Analyzing

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Results of DDJ research depend in increasing manner on
(graphical) display of (automated) data analysis software
Tools and programming languages
● Developers use Python, Ruby on Rails, JavaScript, HTML
● Used third-party software includes MySQL, Access, Excel,
Caspio, Tableau, Arcview, TimelineSetter etc.
(14, 17, 28)
Building and visualizing

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DDJ is connected to a special way of representation which consists
of
● displaying key messages as graphics and/or
● building interactive web applications
Storytelling is done through
(1) interactive web applications with continuous update of data
(2) interactive application based on a stable data set
(3) continuously updated info graphic or
(4) static infographics
(17)
Building and visualizing

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● Working alone at small and medium-sized newspapers, and
part of teams at larger news organizations
● New connections between journalists and programmers
● Members of teams usually have complementary backgrounds
(6, 9, 14, 18)
Collaboration

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● Rise of "annotative journalism"
● Regarding the collaboration between newsroom and ICT-
department in media corporations data journalists perceive
the relation as troublesome.
Rather data journalists try to bypass ICT department when
installing extra software or setting up databases or servers
(6, 28)
Collaboration

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● The goal of DDJ activities is by definition the [very accurate]
journalistic publication
● Publication of data sources and raw data following open data
principles is mentioned too as an integral part of DDJ.
(6, 17, Coddington, 2014)
Publishing the product

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Backgrounds of data journalists

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Backgrounds of data journalists
● Data journalists are appx. 5 years younger than the average
age of German journalists
● All of them have started a university program, 80% have also
finished it
● There is no generalizable “data journalism” career path.
Background is mostly either social science or informatics.
● Backgrounds include programming, design, typography, info
graphics, usability, databases, Web and journalism
● USA: dominance of National Institute for Computer-Assisted
Reporting (NICAR)
(14, 17, 18; 6)

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Enabling and Hindering Factors

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Enabling and indering factors
Critical factors
● Skills of the involved journalists
● Support networks (internal and external) important for the
development of skillsavailability of data
● Tools
● Legal resources
● Available resources
(6, 14, 17)

MEDIA & DESIGN
@julauss, @sextus_empirico & @oppermann_m 47#DuMD2015 & #DUMediaDays
● New kind of people arriving in the newsroom
● New skills needed in the newsroom
● Increase of collaborative newswork
● Shift to data-driven approaches (and
epistemologies debates connected to that)

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Scope:
● Practices outside of Europe and North America
● The construction of "facts"
● Gender aspects
Methods of data collection:
● Survey
● (Participant) observation
● Content analysis
● Digital methods
Research gaps

MEDIA & DESIGN
49
Explore the (preliminary) corpus
online – it's a protoype:
http://tinyurl.com/valid-survey
http://validproject.at
,
@julauss
julian.ausserhofer@fh-joanneum.at
Robert Gutounig1
&
@sextus_empirico
robert.gutounig@fh-joanneum.at
Michael Oppermann2
@oppermann_m
michael.oppermann@univie.ac.at

MEDIA & DESIGN
Tools & Literature
50

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51
NVIVO [Computer Software]. (2015). Retrieved from http://www.qsrinternational.com/
Bostock, M., Ogievetsky, V., & Heer, J. (2011). D³ data-driven documents.Visualization and Computer
Graphics, IEEE Transactions on, 17(12), 2301-2309.
Lopez, P. (2009). GROBID: Combining automatic bibliographic data recognition and term extraction for
scholarship publications. In Research and Advanced Technology for Digital Libraries (pp. 473-474). Berlin:
Springer.
Zotero [Computer Software]. (2015). Retrieved from http://zotero.org/
Tools & software libraries

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52
Anderson, C. W. (2013). Towards a Sociology of Computational and Algorithmic Journalism. New Media &
Society, 15(7), 1005–1021. http://doi.org/10.1177/1461444812465137
Anderson, C. W. (2015). Between the Unique and the Pattern: Historical Tensions in Our Understanding of
Quantitative Journalism. Digital Journalism, 3(3), 349–363. http://doi.org/10.1080/21670811.2014.976407
Cox, M. (2000). The Development of Computer-assisted Reporting. Presented at the Newspaper Division,
Association for Education in Journalism and Mass Communication, Southeast Colloquium, Chapel Hill, North
Carolina.
Fink, K., & Anderson, C. W. (2015). Data Journalism in the United States: Beyond the "Usual Suspects".
Journalism Studies, 16(4), 467–481. http://doi.org/10.1080/1461670X.2014.939852
Garrison, B. (1996, September). Computer-Assisted Reporting: A National Use Update. Presented at the
National Society of Professional Journalists Meeting, Washington, D.C.
Lewis, S. C. (2015). Journalism In An Era Of Big Data. Digital Journalism, 3(3), 321–330. http://doi.org/10.
1080/21670811.2014.976399
Loosen, W., Reimer, J., & Schmidt, F. (2015). When Data Become News: A Content Analysis of Data Journalism
Pieces. Presented at the The Future of Journalism 2015 Conference, Cardiff.
Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work,
and Think. Boston: Houghton Mifflin Harcourt.
Primary Sources

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53
Massaro, M., Dumay, J. C., & Guthrie, J. (forthcoming). On the Shoulders of Giants: Undertaking a Structured
Literature Review in Accounting. Accounting, Auditing & Accountability Journal.
Meyer, P. (1973). Precision Journalism: A Reporter’s Introduction to Social Science Methods (2nd ed.). Oxford:
Rowman & Littlefield.
Russ-Mohl, S. (2006). The Economics of Journalism and the Challenge to Improve Journalism Quality: A
Research Manifesto. Studies in Communication Sciences, 6(2), 189–208.
Thomas, J., Harden, A., Oakley, A., Oliver, S., Sutcliffe, K., Rees, R., … Kavanagh, J. (2004). Integrating
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http://doi.org/10.1136/bmj.328.7446.1010
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence-Informed
Management Knowledge by Means of Systematic Review. British Journal of Management, 14(3), 207–222.
http://doi.org/10.1111/1467-8551.00375
Primary Sources

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Corpus 1/3

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Times. Digital Journalism, 3(3), 381–397. http://doi.org/10.1080/21670811.2014.976409
Corpus 3/3

MEDIA & DESIGN
57
Explore the (preliminary) corpus
online – it's a protoype:
http://tinyurl.com/valid-survey
http://validproject.at
,
@julauss
julian.ausserhofer@fh-joanneum.at
Robert Gutounig1
&
@sextus_empirico
robert.gutounig@fh-joanneum.at
Michael Oppermann2
@oppermann_m
michael.oppermann@univie.ac.at

News Production Workflows in Data- driven, Algorithmic Journalism: A Systematic Literature Review

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News Production Workflows in Data- driven, Algorithmic Journalism: A Systematic Literature Review