NYU Data Science newsletter – August 29, 2016

NYU Data Science Newsletter features journalism, research papers, events, tools/software, and jobs for August 29, 2016


Data Science News

81 | The Hustle with Mahir Yavuz and Jan Willem Tulp

Data Stories; Enrico Bertini, Moritz Stefaner and guests, Mahir Yavuz and Jan Willem Tulp

from August 25, 2016

This week we have Mahir Yavuz and Jan Willem Tulp on the show to talk about navigating the business side of data visualization. Mahir is Creative Director of Data Science and Visualization at R/GA and Jan Willem is a data visualization freelancer and founder of Tulp Interactive.


This audacious study will track 10,000 New Yorkers’ every move for 20 years

Vox, Brian Resnick

from August 26, 2016

“Over the next few years, Paul Glimcher and his team are going to recruit 10,000 New Yorkers and track everything about them for decades.”

“By everything, I mean full genome data, medical records, diet, credit card transactions, physical activity, personality test scores, intelligence test scores, social interactions, neighborhood characteristics, loan records, time spent on email, educational achievement, employment status, sleep, GPS location data, blood work, and stool samples.”


A Math Nerd Wants to Stop the Big Data Monster


from August 24, 2016

The decision to leave her job as a tenure-track math professor at Barnard College and join hedge fund D.E. Shaw in 2007 seemed like a no-brainer. Cathy O’Neil would apply her math skills to the financial markets and make three times the pay. What could go wrong?

Less than a year later, subprime mortgages imploded, the financial crisis set in, and so-called math wizards were targets for blame. “The housing crisis, the collapse of major financial institutions, the rise of unemployment—all that had been aided and abetted by mathematicians wielding magic formulas,” she writes in Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Crown, $26).


Data Geeks Are Taking Over Economics

Bloomberg View, Noah Smith

from August 25, 2016

For a few decades, economists used to imagine how the world works, write down a theory describing their idea, and call it a day. If some statisticians came along and found some support for the theory, well, great! But usually they didn’t, and that was fine too. As one old joke put it, if an idea worked in practice, economists would ask whether it worked in theory.

That began to change in the late 1980s and 1990s. As my Bloomberg View colleague Justin Fox has documented, that was when the discipline started shifting toward empirics and evidence.

The key was the explosion of affordable information technology that made it easier to gather and analyze data.


ICML 2016 Plenary Talks


from August 28, 2016

Presentations by: Susan Athey, Fei-Fei Li, David Blei & John Lafferty, Daniel Spielman, Christos Faloutsos


Summer school data science research could trigger real world changes

Microsoft Research, John Kaiser

from August 26, 2016

Microsoft Research hosted its third annual Data Science Summer School in New York City as a diverse group of undergraduate students deployed some of the latest data crunching techniques on millions of rows of anonymized data in an effort to uncover useful information.

“We’re really hoping to give them a flavor of solving a research problem that hasn’t yet been solved,” said Jake Hofman, one of several Microsoft Research instructors leading the intensive eight-week hands-on course that concluded in August. Coursework for the program is freely available on Github.


Inside Facebook’s (Totally Insane, Unintentionally Gigantic, Hyperpartisan) Political-Media Machine

The New York Times Magazine, John Herrman

from August 24, 2016

Facebook, in the years leading up to this election, hasn’t just become nearly ubiquitous among American internet users; it has centralized online news consumption in an unprecedented way. According to the company, its site is used by more than 200 million people in the United States each month, out of a total population of 320 million. A 2016 Pew study found that 44 percent of Americans read or watch news on Facebook. These are approximate exterior dimensions and can tell us only so much. But we can know, based on these facts alone, that Facebook is hosting a huge portion of the political conversation in America.

The Facebook product, to users in 2016, is familiar yet subtly expansive. Its algorithms have their pick of text, photos and video produced and posted by established media organizations large and small, local and national, openly partisan or nominally unbiased. But there’s also a new and distinctive sort of operation that has become hard to miss: political news and advocacy pages made specifically for Facebook, uniquely positioned and cleverly engineered to reach audiences exclusively in the context of the news feed. These are news sources that essentially do not exist outside of Facebook, and you’ve probably never heard of them. They have names like Occupy Democrats; The Angry Patriot; US Chronicle; Addicting Info; RightAlerts; Being Liberal; Opposing Views; Fed-Up Americans; American News; and hundreds more. Some of these pages have millions of followers; many have hundreds of thousands.

Using a tool called CrowdTangle, which tracks engagement for Facebook pages across the network, you can see which pages are most shared, liked and commented on, and which pages dominate the conversation around election topics. Using this data, I was able to speak to a wide array of the activists and entrepreneurs, advocates and opportunists, reporters and hobbyists who together make up 2016’s most disruptive, and least understood, force in media.


Nonstop Benioff: Inside The Master Networker’s Audacious Plan To Disrupt Salesforce — And The World

Forbes, Alex Konrad

from August 24, 2016

Two months hence, at Salesforce’s gargantuan Dreamforce conference, which draws 170,000 people to San Francisco, Benioff will unveil the product he claims will steer the company to a new decade of growth. Its name: Salesforce Einstein, which explains the schmaltzy German–and the extravagant predictions. “If this is not the next big thing, I don’t know what is,” says the CEO of the world’s fourth-biggest enterprise software company.

Einstein, whose details are being revealed here for the first time, explains a lot of things. Why Benioff spent $390 million two years ago to acquire a hotshot young lieutenant, 35-year-old Steve Loughlin, and his responsive e-mail and calendar product, and why Salesforce has gobbled up at least half a dozen artificial intelligence startups in the months since. Why the CEO of one of those acquisitions, MetaMind’s Richard Socher, a longtime Stanford academic specializing in AI, will now build the company’s first-ever pure research lab. And why after 17 years running Salesforce, Benioff can still get excited about his own products like a kid who’s found a new toy.


The price of complexity in financial networks

Proceedings of the National Academy of Sciences; Stefano Battiston, Guido Caldarelli, Robert M. May, Tarik Roukny, and Joseph E. Stiglitz

from August 23, 2016

Estimating systemic risk in networks of financial institutions represents, today, a major challenge in both science and financial policy making. This work shows how the increasing complexity of the network of contracts among institutions comes with the price of increasing inaccuracy in the estimation of systemic risk. The paper offers a quantitative method to estimate systemic risk and its accuracy. [full text]


CEO Personality and Firm Policies

Harvard Business School, HBS Working Knowledge

from August 23, 2016

This study analyzes the linguistic content of the Q&A portion of more than 70,000 conference calls in order to explore the relationship between individual traits of senior executives, the investment and financing choices made by these executives, and firm performance. Among the findings, openness is positively associated with R&D intensity and negatively associated with net leverage. Conscientiousness is negatively associated with growth. In performance tests, extraversion is negatively associated with both contemporaneous and future return on assets and cash flow.


Baidu Has Created An AI-Powered Personal Assistant To Deliver Smart Sports Commentary


from August 25, 2016

Through new, innovative uses of artificial intelligence, Baidu has created a personal assistant which produced machine generated, real-time commentaries for the recently finished Olympic basketball games in Rio. The assistant is named Duer and it can give live commentaries in natural languages alongside GIF’s and specific user comments. The personal assistant which was launched in September of 2015 doesn’t just announce basketball games, it’s also used to book restaurants and order takeout along with many other things.


IHE Points to OMS CS as Business Model for Higher Ed Tech

Georgia Tech, College of Computing

from August 26, 2016

In a recent webinar, “Technology and the Evolving Business Model in Higher Education,” Inside Higher Ed (IHE) pointed to the development of Georgia Tech’s online Master of Science in Computer Science (OMS CS) as a prominent case study.

Hosts Scott Jaschik and Doug Lederman, of the IHE editorial team, explored the impact technology has made on the higher ed community — including flipped classrooms, massive open online courses (MOOCs), badging and learning analytics. Georgia Tech’s OMS CS was cited alongside MIT as an example of the way MOOC-inspired models have proven impactful in the evolving landscape of online learning.


CrowdEmotion Case Study: Spotify Music Mashup Video

Medium, Sense Makers, Steven Mulvey

from August 26, 2016

Ever imagined about having an automated music playlist that reads your current emotional status? Well now, this future is getting real.

In partnership with Spotify, CrowdEmotion deployed facial coding to develop the world’s first emotion-driven music discovery platform. Spotify currently uses a database analysis system to uncover their users’ music preferences. Hence, Crowd Emotion, exclusively for Huddle, explored the possibility of an emotion-driven music recommendation system. To do so, we focused on what people’s emotional engagement indicate about their music preferences.


Disney Data & Analytics Conference – Disney Data & Analytics Conference

Orlando, FL The Disney Data & Analytics Conference 2016 will bring together over 1,000 executives, managers, and analysts representing over 60 companies and universities, plus multiple divisions of The Walt Disney Company, including Parks & Resorts, Media Networks, Studio Entertainment, and Disney Interactive. — Wednesday-Thursday, August 31-September 1

d3.unconf 2016

San Francisco, CA Galvanize and Google SF; October 16-17, 2016 all day [free]
Tools & Resources

R Packages for Data Access

Microsoft, Revolutions

from August 11, 2016

Data Science is all about getting access to interesting data, and it is really nice when some kind soul not only points out an interesting data set but also makes it easy for you to access it. Below is a list of 17 R packages that appeared on CRAN between May 1st and August 8th that, in one way or another, provide access to publicly available data.


NoSQL Databases: a Survey and Decision Guidance

Medium, Baqend Blog, Felix Gessart

from August 15, 2016

Together with our colleagues at the University of Hamburg, we?—?that is Felix Gessert, Wolfram Wingerath, Steffen Friedrich and Norbert Ritter?—?presented an overview over the NoSQL landscape at SummerSOC’16 last month. Here is the written gist. We give our best to convey the condensed NoSQL knowledge we gathered building Baqend.


Mesa is a agent-based modeling framework in Python

GitHub – projectmesa

from August 18, 2016

Mesa is an Apache2 licensed agent-based modeling (or ABM) framework in Python.

It allows users to quickly create agent-based models using built-in core components (such as spatial grids and agent schedulers) or customized implementations; visualize them using a browser-based interface; and analyze their results using Python’s data analysis tools. Its goal is to be the Python 3-based alternative to NetLogo, Repast, or MASON.



Brown University, Computer Science

from August 27, 2016

3600 U.S. Computer Science professors crowdsourced and available in one online spreadsheet.


Tenured and tenure track faculty positions

Assistant Professor of Marketing

Yale University, School of Management; New Haven, CT

Assistant, Associate, Full Professors (Multiple Openings)

Houston, TX; Rice University

Director, Institute for Cyberscience

University Park, PA; Penn State University

Postdoc, Natural Language Processing, Center for Data Science and Public Policy

Chicago, IL; University of Chicago, Harris School of Public Policy

Postdoc, Ethnographer of Data Science

Seattle, WA; Department of Human Centered Design and Engineering, University of Washington

Postdoc, Brain Injury in Contact Sports (Soccer)

Dallas, TX; University of Texas, Southwestern Medical Center

Postdoc, Deep Learning for Neuroimaging

Dallas, TX; University of Texas, Southwestern Medical Center

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