Assignment #1 - Computational & Data Journalism Critique
Out: February 1, 2016
Due: February 15, 2016 (10am, before class begins)
Overview
The goal of this assignment is to develop and practice a critical stance towards computational and data journalism. You will select a piece of data journalism from a list of provided news articles and write a ~1200 word critique.
Getting Started
You should read all of the assigned reading as well as the recommended reading on computational and data journalism. For instance, The Rhetoric of Data and the Quartz Guide to Bad Data offer a range of issues with data that might give you ideas for critical angles.
Critical considerations might include: data quality (when collected, how collected, who collected, how obtained, how sampled, possible errors), data analysis quality (how data may have been aggregated, filtered, or transformed algorithmically or otherwise), clarity of communication of data (is it accurate and honest), other types of evidence used beside data (e.g. reporting, research), the main argument / story and how it relied (or didn't) on data, what the data adds to the story, if visualization was used (and used effectively to communicate findings), if there was methodological transparency, if uncertainty in the data or model was communicated, if interactivity was included and to what degree, if statistics (including statistical tests, or hypothesis testing) were used, if and how computing was used (does computing accomplish something here that might not have been possible otherwise?). Be sure to consider the validity of the analysis: is there anything that might cast doubts on the conclusions presented? Of the approaches outlined in the reading by Coddington in his paper "Clarifying Journalism’s Quantitative Turn" which does your piece seem to follow?
Some or all of the factors above (as well as others) may apply to your chosen piece. Your task is to decide what is most important and interesting to include in your critique (you only have about 1200 words!). And keep in mind that you may need to do additional research to understand the piece and how it came together (such as methodology or other companion articles). Write your analysis as if you were going to post it to Medium and have other data journalists reading it: in other words, write for your peers.
You should choose one of the following pieces to serve as the object of your critique.
- Anna Maria Barry-Jester et al. Should Prison Sentences Be Based On Crimes That Haven’t Been Committed Yet? Aug. 2015. The Marshall Project / FiveThirtyEight. Article | Methodology
- Amanda Cox. Tax Day: Are You Receiving a Marriage Penalty or Bonus? New York Times. April, 2015. Article
- Nate Silver. The Best And Worst Airlines, Airports And Flights, Summer 2015 Update. FiveThirtyEight. June, 2015. Article | Interactive | Methodology
- Jennifer LaFleur, et al. The Opportunity Gap. ProPublica. Interactive | About | Methodology 1 | Methodology 2
- Joan Biskupic et al. The Echo Chamber - Chapter 1: The Elites. Dec. 2014. Reuters. Article | Methodology
Submission
This is an individual assignment and you may NOT work in groups. All work should be your own: if you happen to find other critical analyses of the piece online be sure to cite and do not plagiarize. Any sources cited should be either linked in the text of your write-up or included in a "references" section at the end.
You will be evaluated based on the clarity of your write-up (easy to follow, accurate), your summary and explanation of the piece (what was done, why, and how important / meaningful the piece is), whether you include a diverse range of critical considerations (e.g. data, visualization, interactivity, statistics, computing, etc.), and how you rationalize your analysis using logic and evidence (citations, links, assumptions, limitations).
Your should submit your write-up of ~1200 words (excessively short or long write-ups will be penalized). Make sure to include some reflection on the assignment: was there something that was particularly challenging?
Mail a PDF (filename of ASGN1_<your lastname>.pdf) of your write-up to Professor Diakopoulos: nad@umd.edu by the due date.