Assertion certainty 4/5 debate potential 1/5

Bloomberg NLP models feed over 100 Bloomberg Terminal screens

Amanda Stent · Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven) · Mar 2, 2018 · at 9:17

Amanda Stent, NLP researcher at Bloomberg, explains how automated news and social media analytics feed financial sentiment windows on the Bloomberg Terminal.

0:00 / 0:13exact quote · 13.5s
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“And they feed over a hundred different screens within the Bloomberg terminal, which provide company trend information, company tweet information, sentiment information, sentiment alerts, tweets on mergers, tweets by the president of the United States, et cetera.”

quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →

More from Amanda Stent

Assertion Supported
Stent: No generic text analytics platform can handle financial language
“There is no on the market generic text analytics platform that can handle this type of language. No way.”
Amanda Stent Mar 2, 2018 ▶ 6:51 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
Disclosure
Bloomberg can automatically generate news articles without humans in two minutes
“And this kind of article we can now automatically generate. So you can get this with no human intervention within two minutes, and then within five minutes a human journalist can come along in art color.”
Amanda Stent Mar 2, 2018 ▶ 8:29 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
Assertion Partly supported
Generic NLP mistakenly linked Bill O'Reilly news to O'Reilly Auto Parts
“Okay, so Bill O'Reilly said something, and there's a small and innocent company called O'Reilly Auto Parts somewhere in the Midwest, and a bunch of generic text analytics engines linked Bill O'Reilly to O'Reilly Auto Parts, and the O'Reilly Auto Parts stock dr…”
Amanda Stent Mar 2, 2018 ▶ 9:48 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
Disclosure
Bloomberg filters social media manipulation using account metadata and supply chain data
“We do a lot of historical monitoring, so we can know how old a social media account is. We also have a very, very large collection of pieces of information about entities in the world, so we can know how closely associated a particular handle is. With a decisi…”
Amanda Stent Mar 2, 2018 ▶ 16:15 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
Disclosure
Stent: Bloomberg shifted data labeling to deep learning and decision trees
“And that's something that historically has been done mostly with rule-based systems, but today we do it with deep learning and a lot of decision trees.”
Amanda Stent Mar 2, 2018 ▶ 13:49 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
Insight
Stent: Earnings call cues cannot reliably predict financial performance
“So we can't always predict based on the non-linguistic or even the linguistic features of a, of an earnings call or an earnings release.”
Amanda Stent Mar 2, 2018 ▶ 23:13 Text Analytics for Finance // Amanda Stent, Bloomberg (FirstMark's Data Driven)
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