Research on data journalism: What is there to investigate? Insights from a structured literature...
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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, Graz2: University of Vienna 3: Humboldt Institute for Internet and Society, Berlin
NODA16 Academic Pre-Conference #NODA16 21.04.2016, University of Helsinki
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*Tool evaluation partners
** *
Supported by:
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Research Interest
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@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)
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How is the research literature developing?
What are the research gaps?
Research questions
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Method
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Structured 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 structured literature review?
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MEDIA & DESIGNUndertaking a systematic literature review
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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 comprehensive literature search
Coding dataDefining the questions that the literature review should answer
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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 comprehensive literature search
● Empirical research on DDJ ● Social science focus, but open to other
disciplines ● Published after 1995
IncludedJournal articlesBook sectionsConference papersReports (from industry and research projects)PhD theses
Not includedBachelor's and Master's thesesPress reportsBlog posts
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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 comprehensive literature search
● Preliminary search with “data-driven journalism”
● Extracting related terms from the keyword section of research papers
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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 comprehensive literature search
Search termsalgorithmic journalismcomputational journalismcomputer-assisted reportingdata journalism
data-driven journalismdata-driven reportingdatabase journalismdatajournalismdatenjournalismus
quantitative journalism
No search termsaccountability journalismcrowdsourced journalismdatavizdatavis
ddjdrone journalisminvestigative journalismonline journalismopen journalism
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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 comprehensive literature search
Scientific DatabasesACM Digital Sowiport
EBSCO Springer
IEEE SpringerLink
JSTOR Taylor & Francis Online
ProQuest Web of Science
Science Direct Wiley
Scopus Google Scholar
Sociological Abstracts
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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 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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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)
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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)
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Results
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Development of the literature over time
n=40
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Publications by type and citations
n=40 bubble size = number of citations in Google Scholar
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MEDIA & DESIGNAffiliations & collaborations
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1787-2015 n=1644
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References per year
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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.
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Gray, J., Bounegru, L., & Chambers, L. (Eds.). (2012). The data journalism handbook: How journalists can use data to improve the news. Sebastopol: O’Reilly.
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Theoretical frames
● Science and technology studies
● Actor network theory(Ausserhofer, 2015; De Maeyer, Libert, Domingo, Heinderyckx, & Le Cam, 2015; Parasie & Dagiral, 2013; Parasie, 2015)
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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.
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MEDIA & DESIGNGeographical 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
… …
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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)
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Conclusion
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● 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
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● practices in small news organizations, freelancers, local and mobile data journalism etc.
● gender
● digital methods: investigating the field through its platforms
● theory
●…
Research opportunities
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Explore the literature online at:
http://literature.validproject.at
Julian Ausserhofer1,2,3, [email protected] @julauss
Robert Gutounig1, @sextus_empirico
Michael Oppermann2, @oppermann_m
Sarah Matiasek1,2 & @sarahmatiasek
Eva Goldgruber1
@evagoldgruber
1: FH Joanneum University of Applied Sciences, Graz2: University of Vienna 3: Humboldt Institute for Internet and Society, Berlin
NODA16 Academic Pre-Conference #NODA16 21.04.2016, University of Helsinki
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References
31
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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
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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