What question did this study set out to answer?

This report aims to introduce a dataset that addresses gaps in existing mass public shooting research.

Introducing Sharing Information to Stop Mass Shootings (SISMS): A Short Report on a Behavioral and Event-Level Dataset for the Study of Mass Public Shootings

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Short report presents SISMS, a dataset identifying behaviors linked to mass public shootings, aiding research and prevention.

This report aims to introduce a dataset that addresses gaps in existing mass public shooting research.
Developed the Sharing Information to Stop Mass Shootings (SISMS) dataset containing data on 171 incidents and 175 perpetrators
Data collection involved public records, official documents, and open-source reporting
Included pre-attack indicators such as grievances, concerning behaviors, and planning details.
SISMS integrates detailed behavioral data and incident characteristics from 1999 to 2024
Confirmed early warning signs such as leakage and planning in over 171 incidents
Provides methodological transparency beneficial for future violence prevention research.

Schildkraut et al. (2026) studied this question.

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