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MEDIA & DESIGN
Research on data journalism:
What is there to investigate?
Insights from a structured literature review
Julian Ausserhofer1,2,3, Robert Gutounig1, Michael Oppermann2,
Sarah Matiasek1,2 & Eva Goldgruber1
1: FH Joanneum University of Applied Sciences, Graz

2: University of Vienna

3: Humboldt Institute for Internet and Society, Berlin
NODA16 Academic Pre-Conference

#NODA16

21.04.2016, University of Helsinki
MEDIA & DESIGN
*Tool evaluation partners
*
*
*
Supported by:
MEDIA & DESIGN
Research Interest
MEDIA & DESIGN
@julauss
Research literature on data journalism
2013: "internalist tendencies at [... the] early
stage of academic research" (Anderson, 2013, p. 1007)
↓



2015: "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)
4#NODA16
MEDIA & DESIGN
How is the research literature developing?
What are the research gaps?
Research questions
@julauss 5#NODA16
MEDIA & DESIGN
Method
MEDIA & DESIGN
Structured literature review
@julauss 7#NODA16
MEDIA & DESIGN
"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 structured literature review?
@julauss 8#NODA16
MEDIA & DESIGN
Undertaking a systematic literature review
9
Adapted from Massaro et al. (forthcoming)
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
comprehensiv
e literature
search
Coding dataDefining the
questions
that the
literature
review
should
answer
@julauss#NODA16
MEDIA & DESIGN
10
Developing
insights and
critique
through
analyzing
the dataset
Developing
future
research
paths and
questions
Coding dataDefining the
questions
that the
literature
review
should
answer
Determining
the type of
studies and
carrying out a
comprehensiv
e 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
@julauss#NODA16
MEDIA & DESIGN
11
Developing
insights and
critique
through
analyzing
the dataset
Developing
future
research
paths and
questions
Coding dataDefining the
questions
that the
literature
review
should
answer
Determining
the type of
studies and
carrying out a
comprehensiv
e literature
search
● Preliminary search with “data-driven
journalism”
● Extracting related terms from the keyword
section of research papers
@julauss#NODA16
MEDIA & DESIGN
12
Developing
insights and
critique
through
analyzing
the dataset
Developing
future
research
paths and
questions
Coding dataDefining the
questions
that the
literature
review
should
answer
Determining
the type of
studies and
carrying out a
comprehensiv
e 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
@julauss#NODA16
MEDIA & DESIGN
13
Developing
insights and
critique
through
analyzing
the dataset
Developing
future
research
paths and
questions
Coding dataDefining the
questions
that the
literature
review
should
answer
Determining
the type of
studies and
carrying out a
comprehensiv
e 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
@julauss#NODA16
MEDIA & DESIGN
14
Developing
insights and
critique
through
analyzing
the dataset
Developing
future
research
paths and
questions
Coding dataDefining the
questions
that the
literature
review
should
answer
Determining
the type of
studies and
carrying out a
comprehensiv
e literature
search
772 search results
↓
Assessment of title, abstract & keywords
- by two independently working researchers

(Thomas et al., 2004)
↓
33 research publications
@julauss#NODA16
MEDIA & DESIGN
15@julauss#NODA16
Records identified
from scientific
databases
(n= 772)
Further publications
from expert poll of
data journalism
researchers (n= 4)
Excluded after
screening
(n= 739)
Preliminary corpus:
publications included
after screening of
records (n= 33)
References from
preliminary corpus
(n = 1151)
Final corpus: Publications
included in the systematic
review (n=40)
Excluded after
screening
(n= 1148)
Further publications
included after screening
of references
(n = 3)
Adapted from Fecher, Friesike & Hebing (2015)
MEDIA & DESIGN
16@julauss#NODA16
software-assisted qualitative
content analysis
(Kaefer, Roper, & Sinha, 2015; Mayring, 2000;
Schreier, 2012; QSR International, 2015)
computational analysis of
structural aspects

(Kreibich, 2016; Lopez, 2009)
MEDIA & DESIGN
Results
MEDIA & DESIGN
Development of the literature over time
n=40
@julauss 18#NODA16
MEDIA & DESIGN


Publications by type and citations
n=40
bubble size = number of citations in Google Scholar
@julauss 19#NODA16
MEDIA & DESIGN
Affiliations & collaborations
@julauss 20#NODA16
MEDIA & DESIGN
1787-2015

n=1644
@julauss


References per year
21#NODA16
MEDIA & DESIGN
Most-cited references
Publication
Nr. of
Citations
Meyer, P. (2002/1973). Precision journalism: A reporter’s introduction to social
science methods (4th ed.). Oxford: Rowman & Littlefield.
15
Parasie, S., & Dagiral, E. (2013). Data-driven journalism and the public good:
“Computer-assisted-reporters” and “programmer-journalists” in Chicago.
New Media & Society, 15(6), 853–871.
15
Gray, J., Bounegru, L., & Chambers, L. (Eds.). (2012). The data journalism
handbook: How journalists can use data to improve the news. Sebastopol:
O’Reilly.
13
@julauss 22#NODA16
MEDIA & DESIGN
@julauss
Theoretical frames
● Science and technology studies
● Actor network theory

(Ausserhofer, 2015; De Maeyer, Libert, Domingo, Heinderyckx, & Le Cam, 2015;
Parasie & Dagiral, 2013; Parasie, 2015)

23#NODA16
MEDIA & DESIGN
@julauss
Research designs & data collection methods
Method Nr. of studies
In-depth interviews 25
Content analysis 21
Survey 5
Short-term observation 3
Newsroom ethnography 1
Note. Content analysis includes analysis of news, databases, blogs, job ads,
visualizations, briefings, manuals, and more. Short-term observation encompasses visits
to the newsroom and participation in meetings. A newsroom ethnography is defined as a
detailed study of a newsroom over the course of several days.
24#NODA16
MEDIA & DESIGN
Geographical scope
Country
Number of
studies
United States 16
United Kingdom 14
Germany 5
International 3
n/a 3
Sweden 2
Switzerland 2
Norway 2
Netherlands 2
… …
@julauss 25#NODA16
MEDIA & DESIGN
@julauss 26#NODA16
Research gaps in data journalism research
● Comparision of practices between countries 

(Appelgren & Nygren, 2014; Parasie & Dagiral, 2013)
● Long-term studies (Davenport, 2000; Knight, 2015)
● Newsroom ethnographies (Parasie & Dagiral, 2013)
● Software studies (Garrison, 1999; Lewis, 2013; Stavelin, 2013)
● Reader experience studies (Segel & Heer, 2010)
MEDIA & DESIGN
Conclusion
MEDIA & DESIGN
@julauss 28#NODA16
● data journalism and its investigation has been
developing rapidly
● quality improvements in the research
● issues with the literature: few publications
refer to theory or methodology, just report
what has been investigated
Conclusion
MEDIA & DESIGN
@julauss 29#NODA16
● practices in small news organizations, freelancers, local
and mobile data journalism etc.
● gender
● digital methods: investigating the field through its
platforms
● theory
● …
Research opportunities
MEDIA & DESIGN
Explore the literature online at:
http://literature.validproject.at
Julian Ausserhofer1,2,3,

julian.ausserhofer@fh-joanneum.at
@julauss
Robert Gutounig1,

@sextus_empirico
Michael Oppermann2,

@oppermann_m
Sarah Matiasek1,2 &

@sarahmatiasek
Eva Goldgruber1

@evagoldgruber
1: FH Joanneum University of Applied Sciences, Graz

2: University of Vienna

3: Humboldt Institute for Internet and Society, Berlin
NODA16 Academic Pre-Conference

#NODA16

21.04.2016, University of Helsinki
MEDIA & DESIGN
References
31
MEDIA & DESIGN
@julauss 32#NODA16
Anderson, C. W. (2013). Towards a sociology of computational and algorithmic journalism. New Media &
Society, 15(7), 1005–1021. doi: 10.1177/1461444812465137
Appelgren, E., & Nygren, G. (2014). Data journalism in Sweden: Introducing new methods and genres of
journalism into “old” organizations. Digital Journalism, 2(3), 394–405. doi:
10.1080/21670811.2014.884344
Ausserhofer, J. (2015). „Die Methode liegt im Code”: Routinen und digitale Methoden im
Datenjournalismus. In A. Maireder, J. Ausserhofer, C. Schumann, & M. Taddicken (Eds.), Digitale
Methoden in der Kommunikationswissenschaft (pp. 87–111). Berlin: digitalcommunicationresearch.de.
doi: 10.17174/dcr.v2.5
Davenport, L., Fico, F., & Detwiler, M. (2000). Computer–assisted reporting in Michigan daily newspapers:
More than a decade of adoption. Presented at the Association for Education in Journalism and Mass
Communication (AEJMC) National Convention, Phoenix, Arizona.
De Maeyer, J., Libert, M., Domingo, D., Heinderyckx, F., & Le Cam, F. (2015). Waiting for data journalism:
A qualitative assessment of the anecdotal take-up of data journalism in French-speaking Belgium.
Digital Journalism, 3(3), 432–446. doi: 10.1080/21670811.2014.976415
Fecher, B., Friesike, S., & Hebing, M. (2015). What drives academic data sharing? PLoS ONE, 10(2),
e0118053. doi: 10.1371/journal.pone.0118053
Fink, K., & Anderson, C. W. (2015). Data journalism in the United States: Beyond the “usual suspects.”
Journalism Studies, 16(4), 467–481. doi: 10.1080/1461670X.2014.939852
Garrison, B. (1999). Newspaper size as a factor in use of computer-assisted reporting. Newspaper
Research Journal, 20(3). Retrieved from http://com.miami.edu/car/baltimore1.htm
Kaefer, F., Roper, J., & Sinha, P. (2015). A software-assisted qualitative content analysis of news articles:
example and reflections. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research,
16(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/2123
Knight, M. (2015). Data journalism in the UK: A preliminary analysis of form and content. Journal of Media
Practice, 16(1), 55–72. doi: 10.1080/14682753.2015.1015801
Kreibich, C. (2016). scholar.py. Retrieved from https://github.com/ckreibich/scholar.py
MEDIA & DESIGN
@julauss 33#NODA16
Lewis, S. C. (2015). Journalism in an era of big data. Digital Journalism, 3(3), 321–330. doi:
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.
Lopez, P. (2009). GROBID: Combining automatic bibliographic data recognition and term extraction for
scholarship publications. In M. Agosti, J. Borbinha, S. Kapidakis, C. Papatheodorou, & G. Tsakonas
(Eds.), Research and Advanced Technology for Digital Libraries (pp. 473–474). Berlin: Springer. Retrieved
from doi: 10.1007/978-3-642-04346-8_62
Massaro, M., Dumay, J. C., & Guthrie, J. (forthcoming). On the shoulders of giants: undertaking a
structured literature review in accounting. Accounting, Auditing & Accountability Journal.
Mayring, P. (2000). Qualitative content analysis. Forum Qualitative Sozialforschung / Forum: Qualitative
Social Research, 1(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/
view/1089
Parasie, S. (2015). Data-driven Revelation? Epistemological tensions in investigative journalism in the age
of “big data.” Digital Journalism, 3(3), 364–380. doi: 10.1080/21670811.2014.976408
Parasie, S., & Dagiral, E. (2013). Data-driven journalism and the public good: “Computer-assisted-
reporters” and “programmer-journalists” in Chicago. New Media & Society, 15(6), 853–871. doi:
10.1177/1461444812463345
QSR International. (2015). Nvivo. Retrieved from http://www.qsrinternational.com/
Schreier, M. (2012). Qualitative content analysis in practice. Thousand Oaks: SAGE.
Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE Trans. Visualization and
Computer Graphics, 16(6), 1139–1148. doi: 10.1109/TVCG.2010.179
Stavelin, E. (2013). Computational journalism: When journalism meets programming (Dissertation).
University of Bergen, Bergen.
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.
doi: 10.1111/1467-8551.00375

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Research on data journalism: What is there to investigate? Insights from a structured literature review

  • 1. MEDIA & DESIGN Research on data journalism: What is there to investigate? Insights from a structured literature review Julian Ausserhofer1,2,3, Robert Gutounig1, Michael Oppermann2, Sarah Matiasek1,2 & Eva Goldgruber1 1: FH Joanneum University of Applied Sciences, Graz
 2: University of Vienna
 3: Humboldt Institute for Internet and Society, Berlin NODA16 Academic Pre-Conference
 #NODA16
 21.04.2016, University of Helsinki
  • 2. MEDIA & DESIGN *Tool evaluation partners * * * Supported by:
  • 4. MEDIA & DESIGN @julauss Research literature on data journalism 2013: "internalist tendencies at [... the] early stage of academic research" (Anderson, 2013, p. 1007) ↓
 
 2015: "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) 4#NODA16
  • 5. MEDIA & DESIGN How is the research literature developing? What are the research gaps? Research questions @julauss 5#NODA16
  • 7. MEDIA & DESIGN Structured literature review @julauss 7#NODA16
  • 8. MEDIA & DESIGN "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 structured literature review? @julauss 8#NODA16
  • 9. MEDIA & DESIGN Undertaking a systematic literature review 9 Adapted from Massaro et al. (forthcoming) 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 comprehensiv e literature search Coding dataDefining the questions that the literature review should answer @julauss#NODA16
  • 10. MEDIA & DESIGN 10 Developing insights and critique through analyzing the dataset Developing future research paths and questions Coding dataDefining the questions that the literature review should answer Determining the type of studies and carrying out a comprehensiv e 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 @julauss#NODA16
  • 11. MEDIA & DESIGN 11 Developing insights and critique through analyzing the dataset Developing future research paths and questions Coding dataDefining the questions that the literature review should answer Determining the type of studies and carrying out a comprehensiv e literature search ● Preliminary search with “data-driven journalism” ● Extracting related terms from the keyword section of research papers @julauss#NODA16
  • 12. MEDIA & DESIGN 12 Developing insights and critique through analyzing the dataset Developing future research paths and questions Coding dataDefining the questions that the literature review should answer Determining the type of studies and carrying out a comprehensiv e 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 @julauss#NODA16
  • 13. MEDIA & DESIGN 13 Developing insights and critique through analyzing the dataset Developing future research paths and questions Coding dataDefining the questions that the literature review should answer Determining the type of studies and carrying out a comprehensiv e 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 @julauss#NODA16
  • 14. MEDIA & DESIGN 14 Developing insights and critique through analyzing the dataset Developing future research paths and questions Coding dataDefining the questions that the literature review should answer Determining the type of studies and carrying out a comprehensiv e literature search 772 search results ↓ Assessment of title, abstract & keywords - by two independently working researchers
 (Thomas et al., 2004) ↓ 33 research publications @julauss#NODA16
  • 15. MEDIA & DESIGN 15@julauss#NODA16 Records identified from scientific databases (n= 772) Further publications from expert poll of data journalism researchers (n= 4) Excluded after screening (n= 739) Preliminary corpus: publications included after screening of records (n= 33) References from preliminary corpus (n = 1151) Final corpus: Publications included in the systematic review (n=40) Excluded after screening (n= 1148) Further publications included after screening of references (n = 3) Adapted from Fecher, Friesike & Hebing (2015)
  • 16. MEDIA & DESIGN 16@julauss#NODA16 software-assisted qualitative content analysis (Kaefer, Roper, & Sinha, 2015; Mayring, 2000; Schreier, 2012; QSR International, 2015) computational analysis of structural aspects
 (Kreibich, 2016; Lopez, 2009)
  • 18. MEDIA & DESIGN Development of the literature over time n=40 @julauss 18#NODA16
  • 19. MEDIA & DESIGN 
 Publications by type and citations n=40 bubble size = number of citations in Google Scholar @julauss 19#NODA16
  • 20. MEDIA & DESIGN Affiliations & collaborations @julauss 20#NODA16
  • 22. MEDIA & DESIGN Most-cited references Publication Nr. of Citations Meyer, P. (2002/1973). Precision journalism: A reporter’s introduction to social science methods (4th ed.). Oxford: Rowman & Littlefield. 15 Parasie, S., & Dagiral, E. (2013). Data-driven journalism and the public good: “Computer-assisted-reporters” and “programmer-journalists” in Chicago. New Media & Society, 15(6), 853–871. 15 Gray, J., Bounegru, L., & Chambers, L. (Eds.). (2012). The data journalism handbook: How journalists can use data to improve the news. Sebastopol: O’Reilly. 13 @julauss 22#NODA16
  • 23. MEDIA & DESIGN @julauss Theoretical frames ● Science and technology studies ● Actor network theory
 (Ausserhofer, 2015; De Maeyer, Libert, Domingo, Heinderyckx, & Le Cam, 2015; Parasie & Dagiral, 2013; Parasie, 2015)
 23#NODA16
  • 24. MEDIA & DESIGN @julauss Research designs & data collection methods Method Nr. of studies In-depth interviews 25 Content analysis 21 Survey 5 Short-term observation 3 Newsroom ethnography 1 Note. Content analysis includes analysis of news, databases, blogs, job ads, visualizations, briefings, manuals, and more. Short-term observation encompasses visits to the newsroom and participation in meetings. A newsroom ethnography is defined as a detailed study of a newsroom over the course of several days. 24#NODA16
  • 25. MEDIA & DESIGN Geographical scope Country Number of studies United States 16 United Kingdom 14 Germany 5 International 3 n/a 3 Sweden 2 Switzerland 2 Norway 2 Netherlands 2 … … @julauss 25#NODA16
  • 26. MEDIA & DESIGN @julauss 26#NODA16 Research gaps in data journalism research ● Comparision of practices between countries 
 (Appelgren & Nygren, 2014; Parasie & Dagiral, 2013) ● Long-term studies (Davenport, 2000; Knight, 2015) ● Newsroom ethnographies (Parasie & Dagiral, 2013) ● Software studies (Garrison, 1999; Lewis, 2013; Stavelin, 2013) ● Reader experience studies (Segel & Heer, 2010)
  • 28. MEDIA & DESIGN @julauss 28#NODA16 ● data journalism and its investigation has been developing rapidly ● quality improvements in the research ● issues with the literature: few publications refer to theory or methodology, just report what has been investigated Conclusion
  • 29. MEDIA & DESIGN @julauss 29#NODA16 ● practices in small news organizations, freelancers, local and mobile data journalism etc. ● gender ● digital methods: investigating the field through its platforms ● theory ● … Research opportunities
  • 30. MEDIA & DESIGN Explore the literature online at: http://literature.validproject.at Julian Ausserhofer1,2,3,
 julian.ausserhofer@fh-joanneum.at @julauss Robert Gutounig1,
 @sextus_empirico Michael Oppermann2,
 @oppermann_m Sarah Matiasek1,2 &
 @sarahmatiasek Eva Goldgruber1
 @evagoldgruber 1: FH Joanneum University of Applied Sciences, Graz
 2: University of Vienna
 3: Humboldt Institute for Internet and Society, Berlin NODA16 Academic Pre-Conference
 #NODA16
 21.04.2016, University of Helsinki
  • 32. MEDIA & DESIGN @julauss 32#NODA16 Anderson, C. W. (2013). Towards a sociology of computational and algorithmic journalism. New Media & Society, 15(7), 1005–1021. doi: 10.1177/1461444812465137 Appelgren, E., & Nygren, G. (2014). Data journalism in Sweden: Introducing new methods and genres of journalism into “old” organizations. Digital Journalism, 2(3), 394–405. doi: 10.1080/21670811.2014.884344 Ausserhofer, J. (2015). „Die Methode liegt im Code”: Routinen und digitale Methoden im Datenjournalismus. In A. Maireder, J. Ausserhofer, C. Schumann, & M. Taddicken (Eds.), Digitale Methoden in der Kommunikationswissenschaft (pp. 87–111). Berlin: digitalcommunicationresearch.de. doi: 10.17174/dcr.v2.5 Davenport, L., Fico, F., & Detwiler, M. (2000). Computer–assisted reporting in Michigan daily newspapers: More than a decade of adoption. Presented at the Association for Education in Journalism and Mass Communication (AEJMC) National Convention, Phoenix, Arizona. De Maeyer, J., Libert, M., Domingo, D., Heinderyckx, F., & Le Cam, F. (2015). Waiting for data journalism: A qualitative assessment of the anecdotal take-up of data journalism in French-speaking Belgium. Digital Journalism, 3(3), 432–446. doi: 10.1080/21670811.2014.976415 Fecher, B., Friesike, S., & Hebing, M. (2015). What drives academic data sharing? PLoS ONE, 10(2), e0118053. doi: 10.1371/journal.pone.0118053 Fink, K., & Anderson, C. W. (2015). Data journalism in the United States: Beyond the “usual suspects.” Journalism Studies, 16(4), 467–481. doi: 10.1080/1461670X.2014.939852 Garrison, B. (1999). Newspaper size as a factor in use of computer-assisted reporting. Newspaper Research Journal, 20(3). Retrieved from http://com.miami.edu/car/baltimore1.htm Kaefer, F., Roper, J., & Sinha, P. (2015). A software-assisted qualitative content analysis of news articles: example and reflections. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 16(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/2123 Knight, M. (2015). Data journalism in the UK: A preliminary analysis of form and content. Journal of Media Practice, 16(1), 55–72. doi: 10.1080/14682753.2015.1015801 Kreibich, C. (2016). scholar.py. Retrieved from https://github.com/ckreibich/scholar.py
  • 33. MEDIA & DESIGN @julauss 33#NODA16 Lewis, S. C. (2015). Journalism in an era of big data. Digital Journalism, 3(3), 321–330. doi: 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. Lopez, P. (2009). GROBID: Combining automatic bibliographic data recognition and term extraction for scholarship publications. In M. Agosti, J. Borbinha, S. Kapidakis, C. Papatheodorou, & G. Tsakonas (Eds.), Research and Advanced Technology for Digital Libraries (pp. 473–474). Berlin: Springer. Retrieved from doi: 10.1007/978-3-642-04346-8_62 Massaro, M., Dumay, J. C., & Guthrie, J. (forthcoming). On the shoulders of giants: undertaking a structured literature review in accounting. Accounting, Auditing & Accountability Journal. Mayring, P. (2000). Qualitative content analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 1(2). Retrieved from http://www.qualitative-research.net/index.php/fqs/article/ view/1089 Parasie, S. (2015). Data-driven Revelation? Epistemological tensions in investigative journalism in the age of “big data.” Digital Journalism, 3(3), 364–380. doi: 10.1080/21670811.2014.976408 Parasie, S., & Dagiral, E. (2013). Data-driven journalism and the public good: “Computer-assisted- reporters” and “programmer-journalists” in Chicago. New Media & Society, 15(6), 853–871. doi: 10.1177/1461444812463345 QSR International. (2015). Nvivo. Retrieved from http://www.qsrinternational.com/ Schreier, M. (2012). Qualitative content analysis in practice. Thousand Oaks: SAGE. Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. IEEE Trans. Visualization and Computer Graphics, 16(6), 1139–1148. doi: 10.1109/TVCG.2010.179 Stavelin, E. (2013). Computational journalism: When journalism meets programming (Dissertation). University of Bergen, Bergen. 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. doi: 10.1111/1467-8551.00375