PEARC20 has ended
Welcome to PEARC20!
PEARC20’s theme is “Catch the Wave.” This year’s theme embodies the spirit of the community’s drive to stay on pace and in front of all the new waves in technology, analytics, and a globally connected and diverse workforce. We look forward to this year’s PEARC20 virtual meeting, where we can share scientific discovery and craft the future infrastructure.

The conference will be held in Pacific Time (PT) and the times listed below are in Pacific Time.

The connection information for all PEARC20 workshops, tutorials, plenaries, track presentations, BOFs, Posters, Visualization Showcase, and other affiliated events, are in the PEARC20 virtual conference platform, Brella. If you have issues joining Brella, please email pearcinfo@googlegroups.com.
Back To Schedule
Thursday, July 30 • 8:00am - 9:40am
NLP Workflows for Computational Social Science: Understanding Triggers of State-Led Mass Killings

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

We leverage statistical and natural language processing (NLP) tools for a systematic analysis of triggers of state-led mass killings. The work advances the application of statistics and NLP in the social sciences and also contributes to scholarly efforts by empirically identifying the prominent triggering events of civilian mass killings. More specifically we seek to understand the timing and dynamics of political violence escalation, by examining systematically how certain types of political events may generate a government's policy of mass killing of civilians. The project provides pathways for the general application of promising NLP and statistical methods to the analysis of social event triggers as gleaned from big data repositories. Key objectives include: 1) To develop open source natural language processing (NLP) dictionaries and inference engines for event identification from texts, which are especially valuable for the analysis of political conflict and 2) Construct and validate a computational workflow to machine code millions of news articles (via NLP) for event identification, from a volume of data orders of magnitude larger than could be manually coded by a team of human readers. Having made considerable progress over multiple semesters, we share the methods and tools that have enabled us to overcome significant computational data analytics challenges.

Thursday July 30, 2020 8:00am - 9:40am PDT