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Data visualization illustration of different charts and abstract connection points for the data. These denote the complex information which is available in the knowledge base.

Knowledge Base

The latest information and guides on how to best understand and use ACLED data.
New website FAQs

Frequently asked questions about our new website and myACLED

Methodology

Documentation on ACLED’s methodology, including how ACLED sources and codes information on political violence and protest.

Use and access guides

General guides on how to use and access the latest ACLED data.

FAQs

A selection of questions frequently asked by users of ACLED data.

Update log

A running log of the latest changes in the ACLED dataset.

API documentation

Examples of how to use the various endpoints of the API, as well as detailed information on how to construct complex queries.

All guides

Use the filters below to find the relevant guides, orclick here to search.

Showing 10 of 77 items

How Somali clan actors are coded in ACLED data

How ACLED codes Somali clan actors

How should we understand references to "antifa" in ACLED's dataset?

Guidance on how references to "antifa" appear in the dataset

Election violence automated tags

This guide explains how ACLED tags "poll-related violence" and "election-related violence."

Conflict categories

The conflict categories act as meta-events that group thousands of incidents into broader conflict dynamics, each built on consistent, transparent criteria. Applied across events from 2020 onward, they help uncover trends and improve analysis.

FAQ: ACLED’s new data structure, terms, and platforms

Frequently asked questions about ACLED's new data and platforms

Ukraine civilian infrastructure automated tags

This guide explains how ACLED codes and tags attacks on civilian infrastructure in Ukraine

Conflict Exposure methodology

Methodology detail for ACLED's Conflict Exposure measure and tool.

CAST methodology

The detailed methodology for ACLED's Conflict Alert System (CAST) includes information on access, how the model was constructed, and how to understand the results.

ACLED’s methodology on Ukraine civilian infrastructure automated tags

A guide to ACLED’s methodology for using automatically generated tags to track events that target or damage energy, health, education, and residential infrastructure in Ukraine.

How to Analyze ACLED’s Notes Column using Natural Language Processing (NLP)

Explore how to use NLP to analyze ACLED's ‘Notes’ column for extracting insights.


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