Taking Action Against Gender-Based Violence

Exploring Solutions and Policy Recommendations for Women’s Safety the UK
Women Rights and Empowerment
Custom Dataset
Non-Profit Organization
Digital Safety and Security
Gender Equality

Women in Data is a UK-based organization that supports women in data science to enhance safety, workplace diversity, and inclusivity. In 2023, Women in Data released ‘The Hidden Reality,’ a nationwide survey that quantifies the societal, social, and economic impact of reported and unreported gender-based violence. Among many profound takeaways, the preliminary analysis found that “70% of women in the UK have experienced an episode of harassment or crime incident in the past 3 years” and “68% of respondents didn’t realise the incident was a notifiable offence”. 

The second phase of the research included the ‘Women’s Safety Hackathon,’ in partnership with The Bright Initiative and Snowflake. Four hundred participants worked together to explore findings, uncover new insights, and deliver recommendations using information from past surveys, crime data, and custom social media datasets provided by Bright Data. The custom datasets included social media posts and comments attached to certain keywords and hashtags like #MeToo, #believesurvivors, #nomeansno and #andrewtate. Additionally, Bright Data collected data from the internet forum, Mumsnet, on all topics and replies from the last year that included the word ‘LTB,’ an acronym for ‘Leave the Bastard.’

The event focused on addressing solutions for violence against women and girls, particularly on understanding perpetrator characteristics, geographic variations, improving reporting and data availability, victim vulnerability, effective support strategies, workplace violence, and its economic impact. The recommendations and analysis completed will be published in the next version of ‘The Hidden Reality’ research and will be used to create policy suggestions for regulators.

Read the Women’s Safety Preliminary Analysis

Learn more about Women in Data