Analyzing Code: What a Critical Code Studies Approach Reveals About the Epistemology of Data Journalism

Abstract

The last decade has seen consolidation of data journalism—defined broadly as reporting involving the collection, analysis, and presentation of quantitative datasets—as an established subfield of journalism. While programming code underlies much of data journalism, few studies focus on it, and almost none examine the code itself. Informed by Critical Code Studies, this study departs from previous efforts by examining the role of both quantitative data and computational analysis in data-driven reporting. Using a sample of 234 GitHub repositories of published news stories in the US, we conduct a content analysis of three separate elements of each story: code, data, and the published article. We then use hierarchical clustering to triangulate across these characteristics and identify groups of stories for qualitative review. Our analysis demonstrates the breadth of data journalism—from major investigations to quick statistical reports—enabled by the combination of abundant data and computational techniques to collect and process that data. We highlight the continued dependence on government data, but also the labor involved in scraping web data, and the use of sophisticated reverse-engineering methods to scrutinize tech corporations. Finally, we make several observations regarding studying GitHub as a data journalism infrastructure.

Keywords:

• Data journalism
• code
• open source
• GitHub
• investigative journalism
• algorithmic accountability
• methodology

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 Since we did not have the news story’s weblink a priori, we imposed the less restrictive condition that at least one weblink in the repository should point to the news website’s domain, such as “nytimes.com.”.

2 https://github.com/nytimes/haiti-debt

3 https://github.com/washingtonpost/data-congress-slaveowners

4 https://github.com/datadesk/homeless-arrests-analysis

5 https://github.com/PublicI/sba-disaster-loans

6 https://github.com/washingtonpost/data-2C-beyond-the-limit-usa

7 https://www.washingtonpost.com/graphics/2019/national/climate-environment/climate-change-america/.

8 https://github.com/BuzzFeedNews/2021-05-tx-winter-storm-deaths

9 https://github.com/datadesk/california-coronavirus-scrapers

10 https://github.com/seattletimes/nursing_homes_staffing_20200925

11 https://github.com/seattletimes/nursing_homes_staffing_20200925

12 https://github.com/BuzzFeedNews/2018-06-nyc-311-complaints-and-gentrification

13 https://github.com/nprapps/trump-tweet-analysis

14 https://www.thetrumparchive.com/.

15 https://github.com/BuzzFeedNews/2018-01-trump-twitter-wars

16 https://github.com/BuzzFeedNews/2018-01-trump-state-of-the-union

17 https://github.com/BuzzFeedNews/presidential-language-notebooks

18 https://themarkup.org/google-the-giant/2021/04/08/how-we-discovered-googles-hate-blocklist-for-ad-placements-on-youtube

19 https://github.com/BuzzFeedNews/2018-01-twitter-withheld-accounts

20 Additional example: https://github.com/theintercept/trial-and-terror-data/commit/7295de62c72b41bc0eef1462f1fcd7e4776fe0ba

21 https://github.com/washingtonpost/data-congress-slaveowners/commit/a64e5de1e68be2dbc3cd2972b8ff9a40ae32eb5b.

22 https://github.com/seattletimes/nursing_homes_staffing_20200925/blob/master/B_scripts/A_Enf_Letters_Step1_Download_PDFs.ipynb

23 https://buzzfeednews.github.io/2018-01-trump-twitter-wars/.

24 https://themarkup.org/google-the-giant/2021/04/08/how-we-discovered-googles-hate-blocklist-for-ad-placements-on-youtube

25 https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html#sklearn.cluster.AgglomerativeClustering