An introduction to crime script analysis for analyzing digital and hybrid criminal activity / by Angus Bancroft.

Format:

Book

Author/Creator:

Bancroft, Angus, author.

Series:

SAGE research methods: doing research online

Language:

English

Subjects (All):

Crime analysis.

Physical Description:

1 online resource.

Place of Publication:

London : SAGE Publications, Ltd., 2022.

Summary:

Situational crime prevention is an incentive control approach to crime reduction which understands criminal behaviour as routinised and opportunity dependent. It aims to make engaging in an illicit activity more difficult, risky, and costly for the criminal and to make it less likely they will realise any gains from it. Crime script analysis (CSA) is one implementation of that approach. It aims to identify what contextual elements facilitate criminal activity and so can be used to interdict it. CSA enumerates the crime sequence, the set of actions and resources necessary to allow the crime to be committed. By identifying each step in the process, CSA allows control conditions to be proposed and tested. Initially derived from studies of offline crime, it is becoming more common in analysing digital and hybrid (combined on and offline) criminal activity. This guide describes the CSA process, which involves identifying three distinct phases: precursors, commission, and resolution/departure. The number of steps in the sequence varies according to the crime being carried out and the necessary level of analysis. The nature of digital and hybrid crime requires some rethinking of the underlying assumptions behind the CSA approach and how they might manifest in an online environment. This guide includes a short case study describing an analysis of a counterfeit currency vendor using the Tor darknet. The coding process is described, and a model crime script is laid out in sequence. The strengths and limits of this approach are discussed.

Notes:

Description based on: online resource; title from PDF information screen (Sage, viewed March 31, 2023).

ISBN:

1-5296-1001-X

9781529610017

OCLC:

1335037189