P. Jeffrey Brantingham

About

P. Jeffrey Brantingham is a professor at UCLA in the Anthropology department. His research focuses on the study of human behavior in complex environments. He employs mathematical and computational models to understand the mechanisms that generate behavioral patterns. Additionally, he utilizes a range of computational methods to learn features of behavioral systems from real-world data. His current research examines crime patterns in space and time, as well as the interaction between online and offline behavioral systems. Brantingham is also the co-editor-in-chief of the Journal of Quantitative Criminology.

Research topics

• Political Science
• Computer Science
• Computer Security
• Law
• Psychology
• Medicine
• Criminology
• Economics
• History
• Linguistics

Selected publications

• Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis

  Journal of Criminal Justice · 2020 · 442 citations

  Senior authorCorresponding

  Governments have implemented social distancing measures to address the ongoing COVID-19 pandemic. The measures include instructions that individuals maintain social distance when in public, school closures, limitations on gatherings and business operations, and instructions to remain at home. Social distancing may have an impact on the volume and distribution of crime. Crimes such as residential burglary may decrease as a byproduct of increased guardianship over personal space and property. Crim…

  DOI

• Is Gang Violent Crime More Contagious than Non-Gang Violent Crime?

  Journal of Quantitative Criminology · 2020 · 55 citations

  1st authorCorresponding
  DOI

• Dynamic topic modeling of the COVID-19 Twitter narrative among U.S. governors and cabinet executives

  arXiv (Cornell University) · 2020 · 48 citations

  Senior authorCorresponding

  A combination of federal and state-level decision making has shaped the response to COVID-19 in the United States. In this paper we analyze the Twitter narratives around this decision making by applying a dynamic topic model to COVID-19 related tweets by U.S. Governors and Presidential cabinet members. We use a network Hawkes binomial topic model to track evolving sub-topics around risk, testing and treatment. We also construct influence networks amongst government officials using Granger causal…

  DOI

• STAR: Boosting Low-Resource Information Extraction by Structure-to-Text Data Generation with Large Language Models

  Proceedings of the AAAI Conference on Artificial Intelligence · 2024-03-24 · 11 citations

  articleOpen access

  Information extraction tasks such as event extraction require an in-depth understanding of the output structure and sub-task dependencies. They heavily rely on task-specific training data in the form of (passage, target structure) pairs to obtain reasonable performance. However, obtaining such data through human annotation is costly, leading to a pressing need for low-resource information extraction approaches that require minimal human labeling for real-world applications. Fine-tuning supervise…

  PublisherOA PDFDOI

• Hate speech and hate crimes: a data-driven study of evolving discourse around marginalized groups

  2023-12-15 · 8 citations

  articleOpen access

  This study explores the dynamic relationship between online discourse, as observed in tweets, and physical hate crimes, focusing on marginalized groups. Leveraging natural language processing techniques, including keyword extraction and topic modeling, we analyze the evolution of online discourse after events affecting these groups. Examining sentiment and polarizing tweets, we establish correlations with hate crimes in Black and LGBTQ+ communities. Using a knowledge graph, we connect tweets, us…

  PublisherOA PDFDOI

Recent grants

• AWARE U.S.-China Cooperative Research on Pleistocene Hunter-Gatherers of the Tibetan Plateau

  NSF · $137k · 2002–2006

• Early Human Occupation of the Tibetan Plateau and the Development of High Altitude Adaptations

  NSF · $190k · 2009–2012

• DHB: Mathematical and Simulation Modeling of Crime Hot Spots

  NSF · $750k · 2006–2009

Frequent coauthors

• Andrea L. Bertozzi

  40 shared

• George Tita

  35 shared

• Patricia L. Brantingham

  Simon Fraser University

  33 shared

• George Mohler

  Boston College

  28 shared

• Martin B. Short

  27 shared

• A. Krivoshapkin

  Institute of Archaeology and Ethnography

  18 shared

• Li Jinzeng

  Santa Fe Institute

  16 shared

• Ya. Tserendagva

  16 shared

Education

• B.A.

  UCLA Anthropology

Similar researchers at University of California, Los Angeles

• Elinor Ochsh-63
• Philippe Bourgoish-55
• Thomas S Weisnerh-51