Using social network analysis to understand offending and victimisation

大都会警察局(MPS)的目标是为每个人保持伦敦的安全。其中一个要素是最大限度地利用从数据和数字技术中获得的见解，以支持合乎道德和有效的预防犯罪做法。现有研究强调分析犯罪和犯罪者网络的重要性，例如，为了更好地了解暴力犯罪受害[1]、儿童性贩运[2]和持刀犯罪[3]的脆弱性。这个项目将探索罪犯和其他特工之间的联系。该项目的目的是开发利用社交网络分析来针对执法和预防行动的技术，以减少暴力。候选人将利用公安部掌握的数据(例如逮捕数据、警方情报)和开源数据(例如社交媒体)来了解我们如何将已知罪犯联系起来，以告知犯罪或受害可能如何引发或表现出来。主题可能包括确定罪犯之间先前存在的关系，罪犯之间的联系方式，以及这些联系的强度、频率和影响。这些措施可以整合到现有的机器学习预测模型中，或用于其他方式，为有效和合乎道德的警察资源目标提供信息。

The Metropolitan Police Service (MPS) aims to keep London safe for everyone. One element is to make the most of the insights that can be gained from data and digital technologies to support ethical and effective crime prevention practices.Existing research highlights the importance of analysing crime and offender networks, for example to better understand vulnerability to violent crime victimization [1], of child sex trafficking [2] and knife crime [3]. This project will explore connections between offenders and other agents. The aim of this project is to develop techniques that use social networking analysis to target enforcement and preventative action to reduce violence. The candidate will work with MPS data holdings (e.g. arrest data, police intelligence) and open source data (e.g. social media) to understand how can we connect known offenders in ways that inform how offending or victimisation may trigger or manifest.Topics might include determining pre-existing relationships between offenders, how offenders are connected to each other, and the strength, frequency and influence of these connections. These measures can be integrated within existing machine learning forecasting models, or utilised in other ways to inform effective and ethical targeting of police resources.