Elements: Data: Sustaining Modern Infrastructure For Political And Social Event Data

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

This project extracts quantitative summaries of political and international conflict events among national and non-state actors across the world by combing news reports across the internet in multiple languages. This generates event data, a machine-coded description of someone doing something to someone else as extracted from news reports. The project focuses on political and social events about conflict and cooperation between governments, individuals, non-governmental organizations, rebel groups, and others. The main goal of this project is to integrate and expand the end-to-end cyberinfrastructure for the robust creation, validation, access, and analysis of political event data by national security, government, academic, and non-governmental actors. A major component of this proposal is to continue to grow the project's engagement with the global event data community. This project extends, produces, and integrates a dynamic, robust system for event data to study sub-national and international conflict processes at a global scale, with applications to the needs of the national security and intelligence communities. Using natural language processing software tools to code event data by annotating the kinds of political events that are of interest to political scientists, international relations scholars, sociologists, and the national security community, the project analyzes contemporaneous news reports in English and Spanish, automatically encodes relevant political events for data analysts, and serves the data along with other open event data via the project websites. The technical challenges include: (1) additional extensions of the multilingual framework to more types of events; (2) smoother updates to political actor dictionaries; (3) robust data querying and linking mechanisms, and analytic tools for the broader research and user community; (4) improved methods for focus location extraction across languages and resolutions. This will improve event data quality and event detection through increased, multi-language comparisons. The multi-lingual extensions of the event encoding software and interface will produce novel methods for detecting and analyzing rare and local events. The proposed database integrations and query optimizations will streamline access to the many open access event datasets that exist, enabling researchers across diverse communities to analyze and compare conflict and political processes. The refinements of the geolocation modules will allow detection of locations from biased training samples, which is an important advancement since some political events, such as human rights violations, tend to occur in locations with low news coverage. The robust and innovative geolocation approaches can be carried over to other domain applications. Scaling the related software and data infrastructure aids the political science, national security and big data research communities. We also will provide robust data linkages across a diverse set of event data from multiple and multilingual news reporting services. The sustainable cyberinfrastructure not only includes the event data coding from news reports, but also analysis tools that include an R package and a thin-client browser-based analysis interface to the data. This sustains the cyberinfrastructure and creates a workforce that is able to work in both science, engineering, national security, and intelligence. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.