Sriya Sarkar

Digital Media-ite, Comedian, Filmmaker

Sriya Sarkar can be found at the intersection of comedy, political issues, and digital media (just off of I-95). A filmmaker and comedian, she recently received her Master's in Integrated Digital Media from NYU's Polytechnic School of Engineering.

The smorgasbord of her work lives here.

Digging Deeper Into Incarceration Data

For our final project, one of the main problems Helen and I ran into was the dearth of information pertaining to our subject: how do incarceration rates affect voter turnout? Actually, it was not the dearth of information so much as a lack of raw datasets. Mostly we were finding incomplete and/or aggregate data that did not paint a full picture. Even though our final project is done, I thought I would do some extra digging and see what I could find now that we have a set narrative determined. 

I did not perform any analysis on them, but here are some further sources I found that Helen and I can look into should we decide to continue expanding the research into our project.

US Election Assistance Commission - in 2014, the EAC put out an all-inclusive report detailing the country's citizens' ability to register to vote and cast a ballot. Their report was split into two: one half covering the administrative aspect of counting ballots, the other on each state's election laws and procedures. The best part? They have raw data sets!

"Punishment and Democracy: Disenfranchisement of Nonincarcerated Felons in the United States" - this may be an old report (written in 2004 by professors from Northwestern and the University of Minnesota) but I think it's crucial for us to understand the current climate of this issue and how it has been addressed in the past, especially because neither of us have any background in this. The most telling aspect of the paper is its conclusions of racial disparity and disenfranchisement, and how it connects to the larger issue of how this relates to a skewed practice of democracy in the US today.

"Does Incarceration Reduce Voting? Evidence about the Political Consequences of Spending Time in Prison from Pennsylvania and Connecticut" - this paper from a number of Yale researchers looks at felon voter turnout, in particular, and found that even those who do have the right (in certain states that allow them) vote in very low numbers. Again, this is existing research we need to look at in order to ascertain how this finding figures into our narrative. 

Bureau of Justice Statistics - the Department of Justice has a surprising trove of data. The problem is, I have no idea what exactly I am looking for. In all honesty, I don't even quite know the difference between probation and parole so this research is a bit out of my league. However, the DOJ's Bureau of Justice Statistics will definitely be a key player in filling in information gaps, particularly in terms of incarceration related numbers and information.  

 

 

Some extra R playtime

When we first covered R a few weeks ago, I did not put as much time into trying to learn it because, in all honesty, I did not think I would use it much. After going through the final project process, however, and speaking with my fellow classmates who all found it incredibly useful, I thought I would go back and put some extra effort into exploring the program and its functionalities.

It still took me a little while to get the hang of it; even with seemingly simple things, such as loading in files. Thanks to my classmate, Sandra, however, I soon got the hang of it. I used an existing dataset from one of our first exercises looking at NYC open data for December 2014. 

Using Kevin Miklasz's R template, I first tried out various summary functions. 

I remember getting a summary count was something I struggled to figure out in D3. The ability to so easily access that information in R was surprising (to me, at least, given my limited experience with both programs).

I also played around with creating a quick bar chart.

The axis needs a little more work but I'm slowly making my way through. I definitely see its value as a data analysis tool, particularly when used before jumping into the visualization phase.

R, Matey...

R. It's a beast. For this week, I learned that a R related program exists, R Studio. It's the same program with a more user-friendly interface.

After loading in my CSV file (my NYC Open Data set from one of the first exercises we did this semester), I looked up a couple tutorials online on the various methods that can be used. 

Helen and I met to brainstorm final ideas and we've come up with some cool ideas oriented around my thesis project which focuses on voter turnout. There is a lot of existing data on the topic and we would like to use Tableau for it, since it is related to Helen's thesis project. 

 

Entering the 3D World with QGIS

Even though I am still learning the basics of D3, I found QGIS to be a fascinating program to work with. 

I recreated the tutorial using MindReader's data at home and found it to be relatively straightforward. I certainly didn't encounter as many problems as I do when working with D3, for instance. I still don't understand how the 3D elements (buildings, for example) are created, but I think if given existing files for those, I would be able to construct something around a dataset. 

But easier said than done, I suppose...

(I couldn't figure out a way to host the visualization, so here is an screenshot for it): Github link


Timeline-ing the Planned Parenthood Debacle

Two weeks ago in class, my group used TimelineJS to map out politicians and their hypocritical political stances as related to their sex scandals. Juicy stuff.

For this exercise, though, I chose to redo my timeline and base it on the Planned Parenthood debacle following the release of several sting videos over this past summer. I felt this issue really dominated the news cycle for several months, even becoming the focus of several presidential campaigns. 

When putting together the timeline, therefore, I focused on three main aspects of the overall story - the videos at the heart of it, the political response (or subsequent actions), and the media's response. There is a plethora of news stories related to this, so the timeline I created just scratches the surface. But even going through the stories on there now it is interesting to see the chain effect, particularly in the beginning. Who would have thought, for example, that it would only take three Youtube videos to convince Louisiana's governor to cut off Medicaid funding to Planned Parenthood? The disconnect between the allegations (and the nature of them) and the political responses they triggered (affecting scores of people with no say in the matter) is truly disconcerting.

NY Hall of Science and Political Speech

I wrote about our data vis activity last week, but here it is again (this time, with pictures!).

Sweta and I partnered together to devise a data-related activity for young visitors to the New York Hall of Science in Queens. The entire class was tasked with coming up with an activity that would be engaging for the youth and hands on, with materials that could be readily available. We began by brainstorming what kids are interested in and we settled on something animal or nature related.

We might have slightly misunderstood the assignment because we tried to focus on using a web based dataset. We stumbled upon an interesting dataset through NYC Open Data that detailed every single tree in every borough. Both of us, as people who grew up in the suburbs, figured that city children would have a very different relationship with trees and nature than we did. We wanted to explore that in some way. 

We didn't quite get around to devising the full activity since we had far too many ideas floating around to condense in such a short time period. in essence, we thought building a garden with recyclable materials, or "planting" their tree on a map of New York would be something fun to do. We also thought maybe there was a way to incorporate elements of the project Manahatta, where children could see the city now and how many trees used to be where they are right now/where they live/where they go to school pre-settlement. 

For the midterm, Helen and I are planning to do a project related to the upcoming Presidential elections. She had an idea about the data visualization equivalent of a debate drinking game. The details of our project can be found here

As for the bubble chart tutorial, I am still making my way through it. 

Bar Charts with D3

First off, last week, Sweta and I partnered together to devise a data-related activity for young visitors to the New York Hall of Science in Queens. The entire class was tasked with coming up with an activity that would be engaging for the youth and hands on, with materials that could be readily available.

We began by brainstorming what kids are interested in and we settled on something animal or nature related. We might have slightly misunderstood the assignment because we tried to focus on using a web based dataset. We stumbled upon an interesting dataset through NYC Open Data that detailed every single tree in every borough. Both of us, as people who grew up in the suburbs, figured that city children would have a very different relationship with trees and nature than we did. We wanted to explore that in some way. 

We didn't quite get around to devising the full activity since we had far too many ideas floating around to condense in such a short time period. in essence, we thought building a garden with recyclable materials, or "planting" their tree on a map of New York would be something fun to do. We also thought maybe there was a way to incorporate elements of the project Manahatta, where children could see the city now and how many trees used to be where they are right now/where they live/where they go to school pre-settlement. 

Who knows? Perhaps, once the semester is over and if we have no job prospects, Sweta and I can revisit this activity and see if there's some way to turn it into a lucrative museum activity. 

In the meantime, I struggled a lot with the bar chart activity. I don't have a very strong coding foundation. HTML and CSS I am quite familiar with. I took one intro to Java class, but am not very strong in that field. I know maybe .1% of Javascript. 

I originally wanted to measure the number of incidents by police precinct on each day. Because of all the difficulties, I simplified it to just the number of incidents on any particular day.  It took me a while to realize that my CSV file needed to contain only the column that I wanted to look at. Because nothing was working with the local file, I tried it with SoQL. This is the SoQL query:

https://data.cityofnewyork.us/resource/u8ac-289r.csv?$where=created_date<'2015-01-01T00:00:00' AND created_date>'2014-11-30T00:00:00' &$select=created_date

Still, nothing happened. I changed the array to be a month instead of a week. So it held 31 items instead of 7, and I modified the forEach loop as well. I replaced all instances of "week" with "month." Still nothing. 

I can't tell if the problem is due to formatting or something along those lines. Again, I'm not well versed in JavaScript so I can't quite tell. My code is almost verbatim what was mentioned in the tutorial. While I did reference numerous other tutorials (including Mike Bostock's and some other D3 bar chart ones), I stuck as closely to the professor's as possible. 

Here is a link to my code in Github. It still does not work. I hope to continue to revise it throughout this week to see what I am doing wrong. 

UPDATE: I got it to work! Sadly, the only way I got it to work was by essentially copying the entirety of the professor's code for the 311 example bar chart. I was initially trying to organize information by date, now it is by day of the week. But whereas before, I didn't have anything working. At least now I am able to see a rudimentary visualization. Here is the result:

Finding datasets

NYC Open Data is a fascinating resource. I used to think data was dry and boring, to be honest. I didn't realize the potential for creation with data until quite recently. 

Originally, when searching for a data set to work with for the time period after Eric Garner's death, I looked for emergency-related information and something protest related, perhaps. 

This was the original set I decided to work with - the information messages received by the Office of Emergency Management about emergency events and important City services for December 2014. 

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But after playing around with the site a little more, I came across this set from the Department of Sanitation of all places - a log of all graffiti instances throughout the five boroughs for December 2014. I wish there was a column for what the graffiti actually said, but I think it is interesting that the police precincts are included in the organization of the data. 

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I attempted to take the data and build a simple bar chart using D3. I do not know Javascript, however, nor D3 for that matter, so I was not able to get it to a functioning state. Hopefully, I can do so by next week, though!

Hello World

Hello! Sriya here. And here's the data you need on me:

  • My background is in film production
  • I'm a comedian
  • I have worked at
    • BBC
    • Comedy Central
    • Discovery
    • Upworthy
    • Other
  • I'm passionate about
    • social advocacy
    • standup comedy
    • finding the perfect GIF for every conversation
    • donuts

All the juicy details can be found in my bio.

I wanted to take this class because I come from a traditional narrative background, both in terms of form and medium, and I want to become versed in more digital storytelling. I have always been a news consumer; only recently did I pick up on the trend of data journalism.

As someone who wants to make politics more engaging and accessible to the public at large, particularly through comedy, I wanted to tap into data visualization because it seems like a creative way to present information that audiences need to know about. 

Mostly, though, and it may be a simplistic reason, but I find the field fascinating and just wanted to learn about it, by golly.

As for an example, I came across this handy little visualization featured in The Guardian to see women's rights around the world. 

I was fascinated by the similarity to the color wheel and the simple aesthetics certainly drew me in. Part of me wonders whether it's not a little overly simplistic in its evaluation of women's rights as it portrays strictly a legal view without taking cultural aspects into consideration. But it's fascinating to interact with regardless, particularly when coming across a country that, on paper, affords women rights but is still culturally oppressive.

There's also this one:

It's a map of San Francisco. A laser cut map of San Francisco. It was cut...with lasers.

And lastly, these clips' relevance may be questionable to a degree, but may we never forget the following two bits of television:

What a funky world we live in. 

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