"Official" April BARUG Meetup

Agenda:
6:30 - Pizza and Networking
7:00 - Michael Quinn, Google LA - Opening remarks
7:10 - Seoyoung Kim, SCU - Detecting Risk through Linguistic Analysis of Corporate Emails and News
7:30 - Gus Class, Google Seattle - Google Cloud Platform for R users
8:00 - Matt Dowle - fread's parallel features and other news from data.table.

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Seoyoung Kim

Title: Zero-Revelation RegTech: Detecting Risk through Linguistic Analysis of Corporate Emails and News

Abstract:We demonstrate how an applied linguistics platform may be used to parse corporate email content and news to assess factors predicting escalating risk or the gradual shifting of other critical characteristics within the rm before they are eventually manifested in observable data and financial outcomes. We fi nd that email content and news articles meaningfully predict increased risk and potential malaise. We also find that other structural characteristics, such as average email length, are strong predictors of risk and subsequent performance. We present implementations of three spatial analyses of internal corporate communication, i.e., email networks, vocabulary trends, and topic analysis. Overall, we propose a RegTech solution by which to systematically and effectively detect escalating risk or potential malaise without the need to manually read individual employee emails.

Link to paper: http://www.seoyoungkim.com/papers/DasKimKoth_RegTech.pdf

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Gus Class

Title: Google Cloud Platform for R users

Abstract:
A survey of ways to take advantage of the Google Cloud Platform's Big Data features from R. In this session, Gus will demonstrate ways that data scientists and statisticians can take advantage of the platform features and scalability of Google Cloud SQL, BigQuery, and DataFlow from R. After this session, you will have a basic understanding of approaches to accessing shared data from Cloud SQL, analyzing large datasets in BigQuery, and scaling data processing with DataFlow from R.

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