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UID:65ac5452-d503-44a1-a551-d63a73de5fb8@nexttoyou
DTSTAMP:20261105T160219Z
DTSTART:20261105T181000Z
DTEND:20261105T191000Z
SUMMARY:Mathematical Biology Seminar - Christina Wang
LOCATION:Engineering Center ECCR 257\, 1111 Engineering Drive\, Boulder\, 
 CO 80309
DESCRIPTION:Christina Wang\, Department of Applied Mathematics\, Universit
 y of Colorado Boulder\n\nModeling the Temporal Dynamics of Protest with S
 elf-Exciting Hawkes-Type Count Processes\n\nProtest activity in the Unite
 d States often manifests as waves shaped by both endogenous self-reinforc
 ing dynamics and external events. While researchers have studied the temp
 oral clustering of specific social movements\, large-scale protest-event 
 data allow systematic examination of these dynamics. This work studies th
 e temporal structure of U.S. protest activity using daily event counts fr
 om the Crowd Counting Consortium (CCC) from 2017 to 2026. We develop a di
 screte-time Hawkes-type model that represents protest activity as an over
 -dispersed self-exciting count process while also accounting for external
  events\, temporal seasonality\, and other effects. A stepwise model comp
 arison shows that each added component improves model fit\, suggesting th
 at these features capture distinct aspects of the protest-generating proc
 ess. The fitted models also show that protest dynamics differ substantial
 ly before and after the George Floyd protest wave. The result suggests th
 at self-exciting count models provide a useful framework for separating r
 ecurring rhythms\, endogenous clustering\, and external shocks in large-s
 cale protest data.\n\nhttp://next-to-u.app/events/65ac5452-d503-44a1-a551
 -d63a73de5fb8
URL:http://next-to-u.app/events/65ac5452-d503-44a1-a551-d63a73de5fb8
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