Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter

6 code implementations • 25 Jul 2020 • Thayer Alshaabi, Jane L. Adams, Michael V. Arnold, Joshua R. Minot, David R. Dewhurst, Andrew J. Reagan, Christopher M. Danforth, Peter Sheridan Dodds

In real-time, social media data strongly imprints world events, popular culture, and day-to-day conversations by millions of ordinary people at a scale that is scarcely conventionalized and recorded.

Cultural Vocal Bursts Intensity Prediction Time Series +1

The growing amplification of social media: Measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009-2020

2 code implementations • 7 Mar 2020 • Thayer Alshaabi, David R. Dewhurst, Joshua R. Minot, Michael V. Arnold, Jane L. Adams, Christopher M. Danforth, Peter Sheridan Dodds

We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content.

Scaling of inefficiencies in the U.S. equity markets: Evidence from three market indices and more than 2900 securities

no code implementations • 13 Feb 2019 • John H. Ring IV, Colin M. Van Oort, David R. Dewhurst, Tyler J. Gray, Christopher M. Danforth, Brian F. Tivnan

Using the most comprehensive, commercially-available dataset of trading activity in U. S. equity markets, we catalog and analyze quote dislocations between the SIP National Best Bid and Offer (NBBO) and a synthetic BBO constructed from direct feeds.