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Computational text analysis on unstructured police data: A scoping review

 

Police reports made following attendance at events such as crashes, domestic violence and theft often contain rich contextual details including indicators of mental health issues or abuse types, and persons/entities involved and their relationships, which are not typically captured in structured administrative data, interviews or official statistics. However, the sheer volume of information along with strict data access protocols render manual analysis impractical. Computational text analysis methods offer a feasible and effective approach to automatically process this underutilized data source.

The research team led by Dr Wilson Lukmanjaya (University of New South Wales) included VISION Research Fellow Dr Darren Cook. The team conducted an overview of studies using computational text analysis (e.g., text mining, natural language processing (NLP)), on unstructured police data, serving as a guide for researchers interested in employing similar methodologies. 

Their article, Computational text analysis on unstructured police data: A scoping review, was conducted in accordance with the PRISMA-SCR guidelines, following the two screening processes (title/abstract and full text screening) and the development of a pre-defined protocol. A search was conducted across seven electronic databases covering the past 20 years.

After removing duplicate entries and screening titles/abstracts and full-text publications, 61 studies met the inclusion criteria. Included studies were published between 2004 and 2024, with most from the United States, Australia and the Netherlands.

The scoping review indicates applications of computational text analysis on unstructured police data have moderate to high performance. Common limitations included variable data quality, with reliability depending on the level of detail provided by the police report’s author, and failure to report ethical implications or methodological limitations.

Computational text analysis can extract key information from unstructured police data. However, future research should clearly report ethics approvals and implications, and methodological limitations. 

Recommendation

  1. Establishing a structured data-sharing framework between law enforcement and researchers is crucial to facilitate access and support high quality, impactful research in this field.

To download the paper: Computational text analysis on unstructured police data: A scoping review

To cite: Lukmanjaya, W., Halmich, C., Butler, T., Cook, D., Karystianis, G. Computational text analysis on unstructured police data: a scoping review. Crime Sci (2026). https://doi.org/10.1186/s40163-026-00272-2

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Perpetration of intimate partner violence and suicide attempt, suicidal ideation, and non-suicidal self-harm: a cross-sectional secondary analysis using the Adult Psychiatric Morbidity Survey

Intimate partner violence (IPV) victimization is associated with suicidal behaviour. Suicidal behaviour may also be raised among those who perpetrate IPV compared to those who do not; general population-based evidence is, however, lacking.

The research team, led by Dr Sophie Carlisle (Nottingham University Hospitals NHS Trust) with VISION researchers Professor Sally McManus, Professor Louise Howard, and Dr Vishal Bhavsar and others, aimed to investigate the associations between using violence against an intimate partner with suicidal thoughts, suicide attempt and non-suicidal self-harm in the past year.

In contrast to previous research focusing on those in contact with criminal justice or health services or with IPV perpetrator programmes, this study presents the first examination of the association between IPV perpetration and suicidality in a recent UK general population sample, which can contribute to the development of a national picture of this association and inform population level strategies to address both suicide and IPV perpetration.

The research team analysed data from the 2014 Adult Psychiatric Morbidity Survey. Logistic regressions estimated associations between IPV perpetration and suicide attempt, suicidal ideation, and self-harm. Associations were estimated for men and women separately, and the team explored interaction in estimates by IPV victimization.

There were greater odds of suicidality and self-harm among self-reported perpetrators of IPV compared to the general population. Many of these associations were accounted for by non-IPV life adversities, IPV victimization and substance use. Improving the identification and management of IPV perpetration, and developing targeted safety planning and interventions for this group could reduce suicide for perpetrators and victims of IPV.

Future research generating adequately powered evidence on differences in these associations based on age or ethnic group, could inform targeted prevention/intervention strategies. Future work assessing the impact of increasing severity, or frequency, of IPV perpetration on risk of suicidality could also be helpful in informing future intervention strategies. Finally, further work should also consider the relevance of suicidality to a variety of harmful behaviours perpetrated within IPV. There remains limited evidence for interventions to reduce suicidality for perpetrators of IPV, including perpetrators who are also IPV victims.

Recommendation

Targeted identification and support for perpetrators of IPV could positively impact responses to suicidality and non-suicidal self-harm.

To download the paper: Perpetration of intimate partner violence and suicide attempt, suicidal ideation, and non-suicidal self-harm: a cross-sectional secondary analysis using the Adult Psychiatric Morbidity Survey

To cite: Carlisle S, Whyte R, Saunders K, McManus S, Oram S, Howard L, Bhavsar V. Perpetration of intimate partner violence and suicide attempt, suicidal ideation, and non-suicidal self-harm: a cross-sectional secondary analysis using the Adult Psychiatric Morbidity Survey. Epidemiol Psychiatr Sci. 2026 Mar 26;35:e16. doi: 10.1017/S2045796026100559. PMID: 41883282.

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Gendered violence and epistemic injustice in Iran: women’s civic aspirations for justice

Iranian women perceive themselves as active participants in overcoming barriers that have historically silenced them. Their perspectives on eliminating violence against women (VAW), with a particular focus on how they challenge the structural and epistemic injustices that underpin such violence, are analysed in a recent publication, Gendered violence and epistemic injustice in Iran: women’s civic aspirations for justice.

In their article, Dr Nadia Aghtaie (University of Bristol), Dr Ladan Hashemi (VISION Senior Research Fellow at City St George’s University of London), and Fatemeh Babakhani (Mehre Shams Afarid, Non-Governmental Domestic Violence Organisation for Women and Children, Urmia, Iran), draw on a qualitative, purposive voluntary sample via an anonymous Instagram survey, chosen for its accessibility and reach among women and girls in Iran. A total of 453 respondents aged 16–59 answered the open-ended question, “Write your views and suggestions regarding violence against women and how to eliminate it,” and their responses were thematically analysed. While this method enabled wide participation, it also introduced likely sampling bias towards internet users—particularly younger, urban, and tech-savvy participants.

Participants identified a wide range of violence, including emotional, physical, sexual, coercive control, and street harassment. However, the most prominent themes that emerged were the need for raising awareness, among both women and men, about what constitutes violence, and the demand for comprehensive legal reforms to address and prevent VAW.

Many responses indicated a desire to reshape cultural and religious norms that have historically contributed to women’s marginalisation. The participants’ narratives highlighted how women’s experiences of violence are frequently dismissed, minimised, or rendered unintelligible in dominant public discourses. By articulating their understandings of violence and proposing solutions, these women actively resisted such injustice and asserted themselves as credible knowers.

Overall, respondents acknowledged the intersecting structural, cultural and religious norms that perpetuate VAW in Iran. Yet their responses were not solely diagnostic; they were also future-oriented and hopeful. They strongly believed that education, awareness-raising and legal reforms are catalysts for change and emphasised the right to be heard and valued as credible sources on their views on VAW.

To download the paper: Gendered violence and epistemic injustice in Iran: women’s civic aspirations for justice

To cite: Aghtaie, N., Hashemi, L. & Babakhani, F. Gendered violence and epistemic injustice in Iran: women’s civic aspirations for justice. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-06952-3

For further information: Please contact Ladan at ladan.hashemi@citystgeorges.ac.uk

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VISION researcher receives funding for secondary data analysis

Dr Annie Bunce, Research Fellow at VISION, received funding from the British Association for Counselling and Psychotherapy for her application, Exploring resilience, self-empowerment and wellbeing outcomes of women referred to specialist domestic abuse counselling services.

With the support of Dr Estela Capelas Barbosa, VISION co-Deputy Director, and in collaboration with Sarah Davidge, Head of Membership, Research and Evaluation at Women’s Aid, Annie will investigate whether and how receiving counselling from a specialist domestic abuse (DA) support service is associated with change in wellbeing.

She will analyse quantitative data from national DA charity, Women’s Aid, which includes information on various aspects of victim-survivors’ wellbeing at the start, during, and end of accessing services. Data analysis will reveal whether victim-survivors who receive counselling experience greater improvements in their wellbeing than those who receive other community-based services.

Annie will also examine whether counselling may be associated with greater wellbeing gains for some groups than others, and whether change in wellbeing is associated with the type/s of abuse experienced and other services received.

The analysis will show which factors influence the effect of counselling on changes in wellbeing the most, and which wellbeing indicators are most improved following counselling.

Findings will be shared via an academic report, blog, policy briefing, webinar and conference presentations.

The research will help to improve understanding of the relationship between counselling and wellbeing in the context of DA, feed into Women’s Aid’s ongoing work to ensure they are measuring the things most important to victim-survivors when it comes to their wellbeing and promote consistency in measuring wellbeing-related outcomes across DA services more widely.

Please contact Annie at annie.bunce@citystgeorges.ac.uk for further information.

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Non-intimate femicide in England and Wales: A ‘continua’ approach

A key pledge in the Labour Party’s 2024 election manifesto was to halve violence against women and girls (VAWG) over the next ten years. It is well known that violence and abuse experienced by women and girls incorporates a multitude of contexts outside of (as well as within) family and intimate relationships, therefore, any strategy aimed at significantly reducing VAWG will need to extend beyond the domestic sphere, including lethal violence. Despite important advances in domestic homicide (DH) prevention in recent years, 55 per cent of adult women (16+ years) killed across England and Wales were not categorized as DH.

Dr Caroline Miles (University of Manchester) and VISION Co-Investigator Dr Elizabeth A Cook (City St George’s University of London) specifically address the killing of women and girls outside of family and intimate relationships, referred to here as ‘non-intimate femicide’ (NIF), in their recently published article, Non-intimate femicide in England and Wales: A ‘continua’ approach.

There have been numerous high-profile killings of women and girls by male strangers in the UK over the past few year (for example, Sarah Everard, Sabina Nessa, sisters Nicole Smallman and Bibaa Henry, and three girls, Bebe King, Elsie Dot Stancombe and Alice Dasilva Aguiar killed in Southport). These cases attracted high levels of public attention as is often the outcome of intense media interest in particular femicides. Attracting less media attention are the killings of women and girls by men with whom they are acquainted but not intimately connected to (or in some cases, not recognized as such). There is currently a dearth of data, knowledge and policy aimed at preventing NIF, a problem which Caroline and Elizabeth strive to redress.

The research underpinning this article derives from the first exclusive study of NIF in England and Wales, presenting a statistical analysis of the victim, suspect and incident characteristics for all cases involving women who were killed by non-intimate partners or family members between 2002 and 2022. Using Homicide Index data for England and Wales (2002–2022), the researchers provide original insight into the victim, perpetrator and incident characteristics in NIF cases, and reveal important differences between intimate and NIF, as well as high levels of missing or poorly recorded data. They argue for a more accurate recording of NIF, alongside a ‘continua thinking’ approach to femicide research, which documents the killing of all women and girls across a range of intimate and non-intimate contexts. Caroline and Elizabeth write that by adopting a ‘continua of violence’ approach to femicide, which recognizes how ‘gender links violence at different points on a scale’, a nuanced and inclusive understanding of femicide can be developed that is not restricted to those categorized as ‘intimate’ or ‘domestic’.

If the current UK Labour Government are to succeed in their 2024 pledge to halve VAWG over a ten-year period, it is crucial that they focus on the whole continuum of lethal VAWG, including those killed by strangers and people known to them in some capacity who are not intimate partners or family members. NIF accounts for substantial proportions of female homicide victimization and although a key focus in recent years has been on learning more about the contexts of DH, the pathways leading to and circumstances surrounding the killing of women outside of intimate and kin relationships remain to a large extent unknown. 

Recommendation

Recent work to improve the recording of femicide and measure sex/gender motivations acknowledges some non-intimate contexts of femicide; however, in order to fully understand the gendered contexts of NIF, it is essential to improve the quality of data recording for all forms of femicide and to mainstream sex/gender motivation data collection across the whole continuum of femicide.

To download the paper: Non-intimate femicide in England and Wales: A ‘continua’ approach

To cite: Caroline Miles, Elizabeth A Cook, Non-intimate femicide in England and Wales: A ‘continua’ approach, The British Journal of Criminology, 2026;, azag005, https://doi.org/10.1093/bjc/azag005

For further information: Please contact Elizabeth (Lizzie) at elizabeth.cook@citystgeorges.ac.uk

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Anastasia Fadeeva shares thoughts on Data Impact Fellowship placement studying healthy ageing

 

Dr Anastasia Fadeeva

VISION researcher and Data Impact Fellow, Dr Anastasia Fadeeva, has written a personal blog, Reflections from being a Data Impact Fellow: a placement in Japan, about her time in the country visiting universities and discussing healthy ageing.

In the blog, Anastasia reflects on her short-term placement at Chiba University and Kyoto University, meeting fellow researchers interested in population health and a focus on studying the ageing population and promoting healthy ageing.

As a Data Impact Fellow, Anastasia is researching the issues of violence in older age, the long-term impacts of violence on mental health, and the lack of reliable data. The placement to Japan is one component of the fellowship.

For further information, please see VISION member awarded Data Impact Fellow to study violence and mental health in older age to find out more about her fellowship or contact Anastasia at anastasia.fadeeva@citystgeorges.ac.uk

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Improving police recorded crime data with natural language processing

Understanding and preventing Domestic Violence and Abuse (DVA) is compounded by long-standing data quality issues in police records. Accurate police-recorded crime data is vital for responding to DVA, yet it often contains missing values and inaccuracies.

Across all crime types, the quality of police data in England and Wales has been a concern. While there have been improvements in overall crime data recording since 2014, individual police forces still encounter difficulties adequately recording instances of DVA in police-recorded crime datasets. 

Correcting poorly recorded or missing data at this scale is non-trivial and beyond the capabilities of manual intervention alone. Fortunately, the increasing availability of computational solutions and machine learning algorithms such as text mining and natural language processing (NLP) can augment, and to a degree, offset much of this processing. NLP is supported by a growing body of interdisciplinary research, which shows that valuable information can be automatically extracted from unstructured data such as crime reports and case summaries through technology.

However, automated prediction systems are not without risk, particularly when applied in sensitive domains such as policing. Data inherently reflects societal biases that poorly designed AI solutions can amplify, and in the context of DVA, these biases may stem from underreporting of marginalized demographic groups or inconsistencies in police recording practices.

In their recent study, Improving police recorded crime data for domestic violence and abuse through natural language processing, VISION researchers Dr Darren Cook and Dr Ruth Weir (City St George’s University of London) and Dr Leslie Humphries (University of Lancashire), evaluated the capability of supervised machine learning models to automatically extract victim–offender relationship information from free-text crime notes in DVA cases.

Both models demonstrated that such tools could serve as cost-effective and efficient alternatives to manual coding, accurately classifying relationship type in around four out of five cases. The incorporation of a selective classification function improved precision for the most challenging cases by abstaining from low-confidence predictions, though at the cost of reduced coverage. This research represents a meaningful step toward addressing concerns about the completeness and reliability of police-recorded crime data.

Recommendation

Given that police-recorded crime lost its status as an accredited official statistic in 2014 due in part to weaknesses in data collection and processing, the application of data science methods to reliably impute missing values offers a promising route to restoring confidence in these records. Police constabularies are encouraged to use the available technology and implement text mining and NLP solutions to extract valuable information from unstructured data such as crime reports and case summaries.

For further information: Please contact Darren at darren.cook@citystgeorges.ac.uk

To cite: Cook D, Weir R, Humphries, L. Improving police recorded crime data for domestic violence and abuse through natural language processing. Front. Sociol., 24 November 2025, Sec. Medical Sociology Volume 10 – 2025 https://doi.org/10.3389/fsoc.2025.1686632

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Reducing young people’s exposure to violence in Lambeth

High Trees Community Development Trust and the Lambeth Peer Action Collective (LPAC) were recently awarded further funding from VISION to co-develop an evaluation framework to measure the impact and value for money of open access youth work and provision on reducing young people’s exposure to violence in Lambeth.

The project draws on an existing collaboration and partnership between VISION, High Trees and LPAC that explored the role trusted adults and safe spaces play in protecting young people from violence. The findings from the original partnership support emerging national data about the role that youth organisations, positive activities and trusted adults play in supporting vulnerable young people. However, existing approaches to evaluation surface challenges about how youth work is measured, monitored and evaluated. Through previous LPAC research with young people, youth practitioners and organisations, the team observed a disconnect between how practice is recognised and valued by young people and how funders, commissioners and policymakers expect impact and value for money to be measured.

This contributes to gaps in the quality, consistency and reliability in evidence, particularly as smaller youth organisations have limited capacity and resources to contribute to large-scale evaluations using established methods. For those offering open access youth work and services, where provisions can be accessed by young people regardless of background or need, demonstrating impact and value for money proves even more difficult as these interventions are longer-term, open-ended and/or unstructured across different settings.

Therefore, building on the previous LPAC research and an initial Cost-Consequence Analysis (CCA) produced by VISION, the aim of the current project is to co-produce an evaluation framework, including components for economic evaluation, that supports youth organisations in Lambeth to measure and demonstrate the impact (and potential value for money) of youth service provision.

For further information on the original research, please see the blog, The story so far: Co-production in Lambeth

For further information, please contact Lizzie at elizabeth.cook@citystgeorges.ac.uk

Webinar: Exploring Natural Language Processing in violence prevention data

This event is in the past.

Do you work with text data in the field of violence prevention?

Are you interested in exploring how Natural Language Processing (NLP) can be used as an analytical tool?

Research Fellow Darren Cook from the UKPRP VISION Consortium and the Violence & Society Centre at City, St George’s, University of London will demonstrate how NLP techniques can be applied to domestic violence and abuse data in an upcoming webinar on 13 November 2025 from 10 – 10:50 am.

What is NLP?

Natural Language Processing (NLP) focuses on the interaction between computers and human language, such as interpreting and categorising free text from police or medical notes. This approach enables machines to understand, interpret, and generate human language in meaningful and useful ways. It allows computers to analyse and process text data, capturing not only the content but also the intent and emotion behind the words.

13 November 2025, 10 – 10:50 am, online only 

To register for the event and receive the Teams link, please email: VISION_Management_Team@city.ac.uk

 

Understanding Violence: The risks for migrants with rising far-right fascism

VISION is pleased to announce the funding for an exciting new project from the Migrants’ Research Network (MRN). The funding will extend and disseminate MRN’s existing work to:

  1. understand the nature of far-right violence against migrants in the UK focusing on sites where MRN is currently engaged,
  2. provide migrants with resources to recognize and understand when significant risk of violence is present, and
  3. catalogue migrant experiences of violence to feed forward to better understanding and future resourcing of violence prevention.

MRN has worked extensively to support migrants, to build a basis for political participation and advocacy of migrant interests, and to recognize and combat violence and discrimination. In an existing piece of work, MRN created a draft of an ‘explainer’ document for migrants living in temporary accommodations, detailing the nature of racism in the UK, and the rise of far-right violence against migrants, what risks migrants may face, how to recognize potentially violent situations, and what support and resources are available to migrants with insecure status who have experienced or fear experiencing violence.

Given the resurgence of far-right activity, this document can provide a crucial resource to support migrants, providing information to help mitigate fear. However, there is also a significant gap in knowledge regarding the types of violence migrants experience, how these experiences integrate across the life course in the context of previous experiences of violence, and how they affect a sense of safety in place.

This project seeks to fill that gap by integrating lived experience perspectives, and knowledge of those who work closely with migrants experiencing violence, such as caseworkers. Those with lived experience would iteratively revise the current explainer document, to be rolled out via various digital outlets, for broader reach.

While the motivation for this project is the basis of longstanding advocacy work, and academic-practitioner knowledge exchange, the objectives will fully integrate lived experience. The final outputs will be a series of social media posts for circulation and an ‘explainer’ leaflet, co-designed for migrants in insecure accommodation regarding far-right violence. Quantitative data in the form of a survey, and qualitative data collected in the course of discussions regarding the types of violence experienced by migrants and the fear of far-right violence, will generate a report to fill a gap in knowledge regarding violence experienced by people with insecure migration status.

For further information, please contact Andri at andri.innes@citystgeorges.ac.uk