The Global Terrorism Database (GTD) documents more than 200,000 international and domestic terrorist attacks that occurred worldwide since 1970. With details on various dimensions of each attack, the GTD familiarizes analysts, policymakers, scholars, and journalists with patterns of terrorism. The GTD defines terrorist attacks as: The threatened or actual use of illegal force and violence by a non-state actor to attain a political, economic, religious, or social goal through fear, coercion, or intimidation. Data collection is ongoing and updates are published annually at www.start.umd.edu/gtd.
Some general findings derived from the GTD involve the nature and distribution of terrorist attacks. For example, about half of all terrorist attacks in the GTD are non-lethal, and although approximately one percent of attacks involve 25 or more fatalities, these highly lethal attacks killed more than 140,000 people in total between 1970 and 2018. The attacks in the GTD are attributed to more than 2,000 named perpetrator organizations and more than 700 additional generic groupings such as "Tamil separatists." However, two-thirds of these groups are active for less than a year and carry out fewer than four total attacks. Likewise, only 20 perpetrator groups are responsible for half of all attacks from 1970 to 2018 for which a perpetrator was identified. In general, patterns of terrorist attacks are very diverse across time and place and the GTD supports in-depth analysis of these patterns.
START researchers use the GTD to conduct statistical analyses of patterns of terrorist attacks, perpetrator groups, and responses to terrorism using innovative analytical strategies. Selected findings from these analyses include: (1) the vast majority of terrorist attacks, including those attributed to organizations that represent the most serious foreign threat to the US, mostly attack domestic targets in their own countries; (2) conciliatory actions by the government are sometimes more effective at reducing terrorist attacks than are repressive actions, (3) perpetrator organizations can be classified into those that desist rapidly and those that desist gradually, if at all, based on the shape of their activity over time; and (4) the groups most likely to persist are those with a rapid pattern of onset, while those with a gradual pattern of onset are more likely to decline quickly.
The database—sourced by unclassified media articles—contains information on multiple dimensions of each event. More than 100 structured variables characterize each attack’s location, tactics and weapons, targets, perpetrators, casualties and consequences, and general information such as definitional criteria and links between coordinated attacks. Unstructured variables include summary descriptions of the attacks and more detailed information on the weapons used, specific motives of the attackers, property damage, and ransom demands (where applicable).
A multi-disciplinary team of University of Maryland faculty members developed the GTD data collection methodology by applying fundamentals of social sciences and computer and information sciences. The process starts with a pool of more than two million open-source media reports published each day. The GTD team combines automated and human workflows, leveraging the strengths and mitigating the limitations of each, to produce rich and reliable data.
- Initial Boolean filters of articles.
- Natural Language Processing:
- Remove duplicate articles
- Location identification
- Clustering similar articles
- Machine Learning (ML) models identify most relevant articles.
- Present analysts with high-validity, topically clustered source articles.
- Prompt human assessment of sources with unknown validity.
- Prevent creation of duplicate entries.
- Analyst feedback informs ML models.
Research Analyst Tasks
- Assess source validity.
- Review relevant source articles; apply GTD inclusion criteria to identify unique terrorist attacks.
- Populate database with attack characteristics according to established coding rules.
Detailed information including definitions of terms, and data collection methods can be found in the GTD Codebook. Users of the GTD should carefully consider the implications of data collection methods and, in particular, interpret trends over time with caution. Users can find a training module that provides an overview of the GTD and an introduction to using Microsoft Excel to analyze the data on the Using the GTD training page.