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Thomas King, Practical R for Mass Communication and Journalism, Journal of the Royal Statistical Society Series A: Statistics in Society, Volume 183, Issue 1, January 2020, Page 405, https://doi.org/10.1111/rssa.12538
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Data journalism currently relies on spreadsheets, but Machlis thinks that R has advantages. In particular, scripts can be used to download and clean data for regular reports of latest indicators or to generate charts. As so much work goes into cleaning data to make a story, having a log has merit. But R is quite specialized for journalists—is it really worth it?
Much of the book is given over to tips and tricks in particular R packages such as dplyr and to favourite tools like code snippets. Although these are good today, software tends to change rapidly—and why use R: not Python? R requires a high level of ability in general computation and commitment to apply coding in journalism. The book fails to sell the importance of this and lacks the range of impactful examples that might convince. Indeed the main overall weakness of the book is the lack of steer on what may be newsworthy about data stories.
The readership of the book is taken for granted as those who are already committed to pick up R in data journalism by transferring from spreadsheets or sharpening their coding and wrangling skills. But it should also be useful for university courses if associated examples and stories were offered as exercises. It could support part of a curriculum, though the tutor would need to source new data for stories. Undergraduates who are committed to looking at the programming could use it, as the numeracy that is required is of only high school standard.
The niggling doubt about the book remains whether it really supports journalism. Data exist and can be downloaded; we can even tell a story around it: but so what? Any social assumptions that are implicit in the found data are too often introduced in the text but not reflected on. The examples in the coding could easily have been developed to include that content, but the book itself is uncritical journalism. However, when much journalism is now branded as ‘churnalism’—reworking the same content or rehashing a press release—then automating ’listicles’ may be useful.
The book offers more for a journalism course, with support from a tutor explaining the reason for all the details, tips and general wrangling. Certainly I think that R is a better tool for journalists than, say, SPSS, and programming skills may be an advantage for a competitive job market. This may be more readily adopted in the USA where data journalism is more technically developed. It is less relevant for the many students who go on to public relations roles, where data wrangling skills are not required.
In any case the use of statistics is limited to a correlation in a scatter plot on voting. Local democracy is a good example where data are available but not easily accessed nor typically well analysed.
In conclusion, the book shows potential and would be a good extra on a course which already has good resources of target stories to investigate.