Subreddits talking about a particular subject in the last week.

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I attended a session at the Theorizing the Web conference last week about text-based online communities such as Reddit and 4Chan. Text-based communities are ones in which there is a reciprocal relationship between participants and a text: Community members both shape and are shaped by the words that are exchanged in the online conversation.

I’m interested in exploring the kind of language that is being used in subreddit communities. Using an API endpoint I found here and d3.js, I built a simple interactive graph that allows you to see which subreddits have been talking about a particular word in the last week.

See the full visualization here.

You can find the full repository here at GitHub. Some d3.js code below:

Internal Security Zones: Generative instructions for prison design & maintenance.

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As of 2016, the U.S. criminal justice system holds more than 2.3 million people in 1,719 state prisons, 102 federal prisons, 942 juvenile correctional facilities, 3,283 local jails, and 79 Indian Country jails as well as in military prisons, immigration detention facilities, civil commitment centers, and prisons in U.S. territories (source). The American prison population has more than quadrupled over the past 25 years, an increase largely driven by heavier penalties for non-violent offenses (source).

Michel Foucault reminds us that power is not static, nor does it emanate from a center of origin. Rather, power exists in an enmeshed network and is wielded by people or groups by way of “episodic” or “sovereign” acts of domination (source). Power is dispersed and pervasive rather than concentrated, embodied, and enacted. Confirming Foucault’s diagnosis of “modern societies of control” (a term used by Gilles Deleuze), Giorgio Agamben argues that biopower operates in physical spaces known as “zones of exception,” physical spaces in which disciplinary power is exercised (source).

In many cases, the architecture of a prison – the panoptical design, the single, impenetrable cells, the isolation and surveillance – causes prisoners to internalize discipline. I’m interested in the material form of prisons. Who designs them? What do the physical spaces look like? What are the material exigencies of daily life?

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For my project, I decided to generate a series of instructions for constructing and maintaining a prison environment. I used the U.S. Department of Justice’s Jail Design Guide as primary source text. I also included a list of business advice and aphorisms as well as Jorge Luis Borges’ “Library of Babel.”

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I created a template that included (1) a title; (2) a chapter subtitle; (3) a set of instructions; (4) a list of material needs; (5) key questions; and (5) a random photo from the handbook. I then used Markov chains to generate some of the text.

The result sounds something like design instructions for a dystopian prison of the future. Here were some generative texts:

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I’ve built a Flask application that allows you to generate a new text and photo when you click the button “Generate another.” Right now it’s still locally hosted but I plan to push it online soon.

See my full GitHub repository here. Below is a snippet of the Python program I wrote:

Life expectancy of people in U.S. states – an interactive map

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Last week, I found data from The Health Inequality Project detailing the average life expectancy for people who live in various states in America, male and female. I took the information from that dataset and plotted it into an interactive map of the United States.

Check out the interactive map here. 

I’m still troubleshooting some problems with the tooltip, which allows users to hover over each state and display the data from that particular state. I seem to be having trouble pulling the data from the corresponding CSV.

You can see my full GitHub repository here.

Here is the full index.js code:

Final presentation: plastic in paradisum

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plastic in paradisum is a digital, interactive archive of plastic objects I found washed up on the beach at Dead Horse Bay. It’s a creative interrogation of the social processes that confer value on the objects that surround us.

You can visit the full collection & project website here.

To be honest, I was surprised by how much information about each object was available online. I was able to track down full histories of most objects, including information about the manufacturing company, the material, original newspaper advertisements, and other details I did not expect to find.

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Winthrop pHisoHex bottle
Date: 1930-1950
Manufactured: New York, NY
Material: Low density polyethylene plastic
Description:

Winthrop-Stearns Inc. was a pharmaceutical company that underwent several mergers. A 1922 merger resulted in Sterling Drug, an American global pharmaceutical company that was later divided and sold to other pharma companies.

This particular bottle contained pHisoHex (pHisoderm with hexachlorophene), a preoperative cleansing agent for eye surgery. Initially used exclusively by surgeons, the product was later re-marketed to the public as a skin cleanser in the 1950s.

Polyethylene was first manufactured on a commercial scale during the Second World War by the British company Imperial Chemical Industries (ICI) and eventually American companies began to manufacture polyethylene in the U.S. After the war ended, polyethylene was used to create squeezable bottles for antiperspirant. The flexible squeeze bottle emerged in the 1950s as a high density form of polyethylene.

Here is the final presentation I shared with the class:

The feedback I received from the class was extremely helpful. Most notably, our instructor Stefani pointed out that this project invokes feelings of nostalgia, but perhaps not the disgust that we associate with trash. In short, by decontextualizing the objects we tend to forgot that all this stuff was trash when I found it. Another student suggested adding more objects that are identifiably “trash” – a take-away container, a bottle, a plastic bag, etc. I plan to make adjustments to the project as I prepare the project for ITP’s Spring 2016 show.

Highest peaks in U.S. National Parks.

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For this week’s assignment, we were to use d3.js to create a simple graph. I decided to work with a data set I found at R Data Sets that included information about the highest points in national parks.

See the interactive graph here. 

I decided to start with a simple animation using the .transition() tool in d3.js. I also created two functions, mouseenter and mouseleave, that are triggered when you hover your mouse over each bar of the graph.

See my full code here.

And here is the index.js file:

Project update: Plastic in paradisum.

What counts as the material of vital materialism? Is it only human labour and the socio-economic entities made by men using raw materials? Or is materiality more potent than that? How can political theory do a better job of recognizing the active participation of nonhuman forces in every event and every stabilization? Is there a form of theory that can acknowledge a certain ‘thing-power’, that is, the irreducibility of objects to the human meanings or agendas they also embody?

– Jane Bennett, Vibrant Matter: A Political Ecology of Things

This week I continued making 3D scans of the pieces of discarded plastic that I’d found. I need to continue making the 3D scans and figure out the best way to catalogue each item, including information about where and when the item was manufactured, where the item was found, and how long it will take to disintegrate.

A baby doll:

Discarded baby doll

Found: Dead Horse bay, 03/31/2016.
Manufacturer: Unknown
Material: Synthetic rubber (plastic)

A blue bottle:

Discarded hairspray bottle

Found: Dead Horse bay, 03/31/2016.
Manufacturer: Helene Curtis Industries, Inc., Chicago, approx. 1953
Material: Plastic, most likely High-Density Polyethylene (HDPE)
Est. date of decomposition: 2403

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A pink bottle:

Discarded pink bottle

Found: Dead Horse bay, 03/31/2016.
Manufacturer: Helene Curtis Industries, Inc.
Material: Plastic

First memories of the internet.

For this week’s assignment, we were told to conduct an interview with someone and then represent what they were saying visually. I’m interested in digital folklore, so I asked two friends my favorite question: What are some of your earliest memories of using a computer and/or the internet?

Interview #1: Julia Palermo

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Interview #2: Joao CostaFullSizeRender-1

At first I found that it was difficult to engage with the interviewee while I had my eyes down and sketching, but after we got used to the format I found that the interviews weren’t difficult to conduct. I asked questions in order to show that I was listening and engaged while I was drawing. Overall, the two interviewees seemed to enjoy telling me stories about using computers and the internet for the first time.

SmartPharmacist: Redux.

Welcome to SmartPharmacist, Rebecca.

Based on our analysis of your condition, we would suggest you start with a low dosage of Levodivdivphine to treat your bipolar disorder.

Levodivdivphine is a antiparkinsonian drug that is prescribed for bipolar disorder and inflated asshole cancer.

Suggested daily dosage is 5 pills a day taken orally, or rubbing the gel form of the drug on your testy lower thigh.

Once upon a time, individuals suffering from bipolar disorder syndrome were prescribed Concerta and AndroGel, but new advancements in the field of fist Physics has helped doctors better remedy this disorder.

Side effects of Levodivdivphine may include: bloody urine, effective toenail, kidney duplex, penile torsion, prideful asshole, and weight increase.

This week, we learned how to write functions in our Python programs. For my assignment, I revisited last week’s SmartPharmacist .py program I wrote, which gives terrible drug advice based on your symptoms. The outcome of the program is the same, but the code I wrote streamlines a lot of the action that takes place.

I wrote two functions – one that streamlines random.choice() and one that more cleanly creates the drug name.

Here’s the rewrite of the code:

You can find the full repository on GitHub.

Private share of total health spending by country.

Screen Shot 2016-04-06 at 6.58.20 PMFor this week’s assignment, we were to use SVG graphics and data from Gapminder to create a simple data visualization.

I created two simple data visualizations of this data set that shows, by country, private spend on health as a percentage of the total spending on health. Private health expenditure includes direct household (out-of-pocket) spending, private insurance, charitable donations, and direct service payments by private corporations.

The bubble chart

The first visualization was a bubble chart in which the size of each bubble corresponded to the percentage of the share (see it here). While I thought this method was visually compelling, I also felt that the information could be conveyed more accurately through a different visual. Instead of displaying the countries alphabetically, I thought it would be more informative to display them according to spend.

The bar chart

For the second visualization, I made a bar chart that showed the % private health spend for each country out of the total. I ordered the countries from those that had the highest private spending to the lowest. Check it out here.

Analysis

Visualizing this set of data gave me the ability to quickly compare private/public spend between countries and draw some conclusions.

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You can check out my full GitHub repository here.

Other (unrelated) thoughts

We were also asked to respond to a graphic/chart/visual from the website Wait But Why, a popular resource for explaining complex subjects in a simple way. I decided to look at an article that explains the history of Iraq and ISIS. I studied Arabic language/Middle East Studies in college and my undergraduate thesis explored neo-tribalism in Saddam Hussein’s Iraq so I was curious to see if the author of the article got the history right.

I was surprised – the author did a very thorough job explaining the last 100 years in Iraqi history, with particular emphasis on the factors that led to the rise of ISIS. The Sykes-Picot agreement, which is responsible for diving up Iraq and much of the Middle East, is summarized pretty accurately in these two maps:

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Source: Wait but why