MEASURING GEOPOLITICAL RISK WITH OPEN SOURCES: DATA FOUNDATIONS, CODING SCHEMES, AND CHALLENGES
https://doi.org/10.59982/18294359-25.2-mg-20
Abstract
This article reviews how geopolitical risk can be quantified using open-source
intelligence (OSINT) drawn from news media, event databases, social platforms, and complementary
public data. We first define geopolitical risk as uncertainty arising from conflict, terrorism, and
interstate tensions, and then motivate its economic relevance. We then examine four practical
quantification routes: (i) news-based indices that transform media coverage into time-series
signals of risk (e.g., measures in the tradition of the GPR index); (ii) event databases
such as GDELT and ACLED that code protests, violence, and diplomatic actions into
structured records that can be aggregated into frequency and intensity metrics; (iii) social media
and search trend analytics that act as early-warning signals through sentiment and volume shifts;
and (iv) composite, multi-source indices (e.g., trade-risk and market- attention gauges) that
integrate sanctions, deployments, disruptions, and text signals into a single score. Brief case
examples illustrate how these approaches capture historical surges and support operational
decision-making in public and private sectors. We also synthesize key limitations—data overload and
verification, media and regional bias, complex causality, and timeliness trade-offs—and emphasize
the role of human expertise alongside automated analytics. The paper concludes with
implications for researchers and practitioners seeking transparent, reproducible, and
decision-relevant measures of geopolitical instability.
Keywords: Geopolitical Risk, Open-Source Intelligence (OSINT), News-Based Indices,
Geopolitical Risk Index (GPR), Event Data, GDELT, ACLED.
PAGES : 191-197