How does Netflix keep getting it right?

In 2013, Netflix came out with Orange is the New Black, one of the first original series to be debuted on an online streaming network. It was an immediate success, and ushered in years of Netflix continuously “getting it right”: House of Cards, Arrested Development, Unbreakable Kimmy Schmidt, numerous Marvel shows, Sense8 – and, most recently, Stranger Things.

What’s fascinating is that there seems to be pattern of streaming video networks coming out with great original shows while cable TV shows are declining in quality and originality. When Stranger Things came out in early July of 2016, Netflix had another hit, and I heard many people saying in awe, “How does Netflix keep getting it right?”

It turns out there’s a secret to their success: Big Data.

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New Age Research in a New Age World: An Interview with the QAC’s Congressional Politics Research Lab

When seen through a news report or a computer screen, the impact of current political research can seem very disconnected from what’s really taking place. It can be hard to try to understand the results and implications of politician’s behaviors and opinions without an already-written history book. But with this new age of media presentation comes the new age digging tool of data analysis, which is once again proving to be the key to decoding to today’s political discourse.

And that’s not its only use. Once again, Wes students are proving it possible to not only use online politics for research purposes, but to get your foot in the door of Data in the Real World. In April, John Murchison ‘16, Grace Wong ‘18, and Joli Holmes ’17 attended the Midwest Political Science Association conference in Chicago to present a poster about their research on congressional politics.

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Is it our future to be agnostic?

As interest in data and data analysis grows, future students interested in the career have to work harder to understand the boundaries and guidelines. It won’t always be as simple as it was for Evan Thorne ‘15, who came to Wesleyan thinking he wanted to study Economics before discovering the QAC department. “I was starting to work with data sets in my math and computer science classes when I heard about big data,” Evan said, explaining that it was soon after he began taking classes with the QAC that he realized he wanted this as a career.

But what is “this”? Data science? Data analysis? Data manipulation? Sometimes it can be hard to define. But Evan did not flounder when I asked him for a definition of his job at CKM Advisors, the company where he was hired right after graduation. He began by explaining to me that an analyst is someone who is able to take in what’s readily available to them and then dissect it to look at more basic stats and trends. Data scientists, however, are able to find things that aren’t available – unstructured data – and take it in raw. “Every data scientist is an analyst in a way,” Evan explained, “but it’s at a much bigger level.” At CKM, Evan is a data scientist, and he is responsible for all of the analytic process: data ingestion, wrangling, manipulation, analysis, and visualization.

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Data Visualization and the Transparency of Truth

Transparency is a hot issue; in politics, in business, and in journalism, people are all itching to know how truthful the truths their being fed really are. However, truth is no longer as easy a thing to gauge as it once was. It turns out, the public can be fed information that is, technically, true, yet at the same time only one version of the truth.

A good example to look at is weather forecasts. Most people think of weather as easy and straight-forward data to access. There are tons of websites that allow search by location (eg/ www.weather.com), and on TV news we can be given an explanation of a weather chart, as seen below:

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Data from Surprising Origins: Looking at the Work of R. Luke Dubois

When R. Luke Dubois sat down with a group of students for lunch on Friday, November 20th, he could have begun by introducing himself: Known as R. Luke Dubois or just Luke Dubois, he is an artist based in New York City with many notable works related to data, some of which have been on display at the Zilkha Gallery since the beginning of the semester. But instead he began by asking us what we were working on.

At first, most of us nervously fidgeted in silence. We hadn’t been expecting the spotlight to be on us. After a couple awkward moments, I offered up an explanation of my final project for my data analysis class. Dubois responded with interest and gave some suggestions. After that, other students slowly began to come forward with their ideas, and he continued to react excitedly. He then powered up the projector behind him and showed us some related work by other artists, such as Fernanda Viegas and Martin Wattenberg.

After this discussion had gone on for a while, I realized that Dubois wasn’t going to talk about himself or his work unless he was prodded to. I turned the spotlight back on him by asking whether he thinks of himself as an artist or data researcher. Dubois jerked his eyes upwards, and when they re-centered on us he had a funny smile on his face. “I’m a musician,” he responded. “I play the cello badly. I played so badly that I switched to a computer.”

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Data and a Polygraph: A Look into Data Journalism

As the uses and values of data become more well-known, more and more unique ways of exploring and presenting data are emerging to the forefront of the Internet. When Wesleyan invited one of these explorers, Matt Daniels, to give a talk on data journalism and media art, I immediately dug into his portfolio. Daniels hosts his projects on a website called Polygraph, and currently has only focused one exploring data related to music. I was immediately transfixed by the name of his site – polygraph isn’t a word commonly connected to data or information – and, due to blanking on the definition, Googled it. I found the following:

pol·y·graph [ˈpälēˌɡraf]

NOUN

  1. A machine designed to detect and record changes in physiological characteristics, such as a person’s pulse and breathing rates, used especially as a lie detector.

With this definition swirling in my head, I came to Daniels’ talk eager to learn what he was all about. Daniels, one of the many young creators who are storming the tech industry, began by clicking to a slide of the visualization that made him “internet famous.” He describes that the goal of this project was to look at the usage of unique words by rappers in their songs. The visualization charts these usages, along with the amount of unique words used by authors ranging from Shakespeare to Melville. The visualization was then followed by some text that further fleshed out what he had discovered. And there you find Daniel’s formula, the foundation of this data journalism he has fallen into: a code narrative + a prose narrative = an interesting and interactive read.

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Introducing: The Data Analysis Minor

The Quantitative Analysis Center has always had the goal of bringing together students from across different departments and disciplines through the art of data analysis. While data and quantitative analysis can be connected only to work in math and computer science, it is really a broad skill set that can complement work done in economics, psychology, sociology, English, and much more.

Pride yourself on wheedling down a chaotic data set? Enjoy making snazzy graphs? Love seeing stories unfold from visualizations? Finally, there is now a way to officially bring together the QAC’s programs and your main major. With the QAC Data Analysis Minor, these skills can officially be declared as a part of your college education. Overall, this five course minor requires one basic knowledge course; two courses that are either mathematical, statistical, or computing foundation courses; and two applied electives. Not bad, eh?

I know what you’re thinking. Finally there is a way to learn how to master messy data and make snazzy graphs and get credit for it on your college diploma. So what are you waiting for? Acquire this awesome skill set, enter the world of the QAC, and declare your data analysis minor today!

Don’t Count Data Out: A Conversation with Dana Louie ‘14

When I mention that I’m taking classes in the QAC department, I’m often met with blinking eyes and blank stares. Few people know what it is, or if they do they ask something along the lines of: “Oh, that <em>data</em> thing?” They say data like it’s some sort of disease that is not understandable or conquerable.

Data is far from a disease, but it <em>is</em> capable of spreading everywhere. Data are not static numbers on a screen; data are what is behind your favorite <em>New York Times</em> article. Data is extremely customizable and manipulatable and, most importantly, for everyone.

Despite those who have never heard of the QAC before, the department has been running at Wesleyan for years, and many now graduated students stumbled their way into their first QAC class only to leave with a career in data analysis. One of those students is Dana Louie ’14, who I had the pleasure of chatting to when she came to campus to give an info session for Analysis Group, the firm she works for. Dana’s discovery of the QAC happened through the QAC summer program, where she took classes in morning and then worked on research with professor in the afternoon. The following year, she was selected to be QAC tutor, and her fate in the department was sealed.

“People can succeed [in QAC classes] even with no background,” Dana said confidently, referring to the fear that keeps a lot of students from getting off the bench and entering the world of the QAC. When talking with my friends about by own experiences in the QAC, they often say something along the lines of “Wow, that sounds really cool. I wish I could do that.” I always respond with “You can,” just as Dana as saying. There are many intro classes in the QAC (QAC201, QAC211), and many chances to start to learn one of the programming languages.

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