Artificial Intelligence

NLP in Computational Journalism: notes from the field at the New York Times

When:
Thursday, October 03, 2019, 11:00am - 12:00pm PSTiCal
Where:
CR# 689
This event is open to the public.
Type:
NL Seminar
Speaker:
Alexander Spangher (USC/ISI)
Video:
https://bluejeans.com/684525530
Description:

Abstract: Computational journalism is an emerging field seeking to enhance traditional journalistic processes -- story finding, production, distribution, funding, evaluation and security using computational techniques. Such advances comes at a critical time: journalists' ability to play a watchdog role in society is severely endangered by industry contraction and budget shortfalls.

Many exciting developments in computational journalism require research in NLP. In this talk, I'll discuss some prior work at the New York Times, including generative localized news articles, human-in-the-loop chat-bots, personalization, and coverage-pattern modeling. I'll also discuss long-term challenges we identified in a broad survey article done at Stanford University this summer, as well as my current research directions here at USC.

Biography: Alex Spangher was a data scientist at the New York Times, where he worked with journalists and newsroom stakeholders on data science to improve journalism coverage and revenue. He interned at Microsoft Research and spent a year as a PhD student at Carnegie Mellon University before transferring to the University of Southern California to work with Emilio Ferrara and Nanyun Peng. He has an M.S. in Journalism and an M.S. in Data Science from Columbia University, and received his B.S. from Columbia as well, in neuroscience and computer science. He enjoys playing classical piano and double bass.

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