KD – Data Cultures

Posted on December 16, 2018 by KD

Reading response 5: Australian movies

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The thing I liked the most about this reading that it investigates a popular notion : “‘10% rule’ to predict the popularity of Hollywood titles in Australia, expecting American films to earn around one-tenth of their domestic box office receipts”. I think this sort of research is very important, because we should have scientific support behind claims that might impact how millions of dollars are distributed. I often ask myself what my fellow classmate did: Is this study even relevant? . Considering the economic implications, here we can firmly say, yes, it is relevant. I also really like the idea that you take data that’s sort of floating out there and you bring it together to say something new.

Posted on December 16, 2018 by KD

Reading response 4

I think this was my favorite reading this semester. I find it super interesting to think about how we can use social media data for research and how it has been used. I think this article does a great job of giving a matter-of-fact run down of the benefits and dangers of using social media data, without glorifying it or demonizing it. Another great thing that it’s an easy to understand reading, and as my classmate PE noted: “data should be findable, accessible, interoperable and reusable to all in order for it to be considered fair data”.

Posted on November 1, 2018 by KD

A cool study, but is it anything more than that?

I liked how the spread of prints was embedded in a historic context. It would have never been possible for printmaking to flourish without the golden age of the Netherlands. While the authors were unable to identify the historic events behind the inward shift experienced by printmakers across Europe, an effort was made to do so. We also learnt that population changes were the largest determinants of changes in printmaking.

While I thought it was a nifty paper, a thought kept resurfacing; so what? Or as a classmate of mine put it, “Is this study even relevant?”. Now we know all this info about printmaking, but how is it going to make anything better, or even affect anything, outside of academic circles. I had a hard last couple of months (years) with this opinion, as this is not an overly helpful view to have in college.

Posted on October 23, 2018 by KD

Don’t expect too much from tools: the limitation of text analysis

I loved this reading. It was easily digestible and interesting. It assumed that I knew nothing, which was correct, so everything was explained in a way I could understand.

I had a couple main takeaways that I’ll summarize here:

Computers can only do whatever you tell them to, therefore they are subject to potential bias. For example, in the very first example, regarding the adjective that described NFL players, the team who put together the program could have compared two different races, or players above and below a certain height, leading us to very different conclusions.
These tools are limited. They cannot *understand* the meaning behind the strings they are encoding. They don’t have a sense of morality and cannot solv problems for us that we do not understand.

Posted on October 4, 2018 by KD

So fewer people go back to prison, but our institutions really suck at reporting stats, huh?

Reading the Pew research on recidivism, and seeing loads of important info missing (tons of states, people who died in the examined period, people who got arrested in other states etc.), my first instinct was to shout “False! The data and the research is shady! Case closed!” (a bit like Jonathan in his response, but less eloquently). But then I thought of something that came up in a group discussion in class in relation to the Eviction Lab reading, namely, that sometimes you just have to do the best you can with the data that’s available, and maybe having stats from lackluster data is better than not having any.

Therefore I think we should think about the responsibility of government institutions in compiling and publishing reliable data on important issues such as recidivism.