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Title:Automatically identifying people shot by police from media sources
Author(s):Satapathy, Sidhartha
Advisor(s):Hockenmaier, Julia
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Natural Language Processing
Police Shooting
Artificial Intelligence
Deep Learning
Machine Learning
Text Classification
Event Extraction
Abstract:Despite several instances of societal attention and widespread protests, there is no database of police-involved fatal shootings. To this end, it is extremely important to develop a system that will monitor media reports of police use of force in nearly real time. In particular, my thesis leverages the recent developments in the field of text classification and event extraction to achieve this goal. In order to develop a database of police-involved fatal shootings, we propose a multiple layer structure. The first layer is a Boolean query to extract articles from the Solr database which stores articles scraped from the internet. We then show various comparisons on how text classification performs in this domain and show a comprehensive analysis of the errors such a system makes. Finally, we show our results on a number of event extraction systems and successfully conclude that using event extraction on top of text classification improves the task of victim name extraction.
Issue Date:2019-04-23
Rights Information:Copyright 2019 Sidhartha Satapathy
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05

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