DSI Professor Helps Launch Data-Science Group at New York Times

Readerscope will help the NYTimes better understand its readers
Readerscope will help the NYTimes better understand its readers


Chris Wiggins, a Data Science Institute professor and Chief Data Scientist at The New York Times, has helped launch nytDEMO, a group at the NYT devoted to bringing data-science prototypes into products. The launch coincides with two AI-driven tools that allow for a better understanding of how the Times’s readers engage with stories.

The nytDEMO (data, engineering, measurement and optimization) group combines data science with designers and developers, and is a partnership with the Times’s Advertising & Marketing Solutions Group. Products are expected to focus on opportunities that support subscription or advertising revenue.

The first product, named “Project Feels,” trains a deep-learning classifier on crowdsourced data to learn a model that predicts readers’ emotional resonance with different stories. As a product, advertisers can choose, for example, that their marketing materials appear only on stories predicted to elicit “hope” or other selected feelings. The second product, “Readerscope,” uses natural language processing to power a graphic user interface for navigating which topics are most read by different user segments, and in which locations.

“Both tools grew out of our internal innovations on how to use machine-learning techniques to better understand our readers,” said Wiggins, associate professor, applied physics and mathematics, Columbia University. “Columbia played a role in Project Feels in particular; it started as a summer internship project between a Columbia College student working with a Data Science Institute graduate in the Data Science Group at the Times.”

nytDEMO is expected to release a series of new machine learning-driven products, growing out of prototypes the Data Science Group has produced to solve newsroom and business problems.  

As an applied data scientist and a founding member of the executive committee of DSI, Wiggins is well-known in industry and academia. He is co-founder of hackNY, a nonprofit that since 2010 has organized student hackathons and the hackNY Fellows program, a structured summer-internship program in NYC startups.

Wiggins is also a senior columnist for Voices, a new DSI blog forum about data science. His most recent essay, “Ethics, Data and Product”, discusses the role of data-powered algorithms in shaping the world and the ethical challenges of artificial intelligence. He also teaches a DSI course called “Data: Past, Present and Future” that explores the interplay between data science, ethics and product development.

In holding two prominent positions – DSI professor and chief data scientist at the Times – Wiggins is in a position to create data-science products while also educating the next generation of data scientists.

“It’s been extremely educational teaching within DSI and also helping the Times, said Wiggins. “Data science is a dynamic field, with academia sometimes leading industry, and industry sometimes leading academia. The two worlds have a long history of benefiting each other, and benefiting NYC as well.”

--By Robert Florida

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