Equally Safe Online

Lead Research Organisation: Heriot-Watt University
Department Name: S of Mathematical and Computer Sciences

Abstract

We address the timely topic of online gender-based violence (GBV): Almost 1 in every 2 women and non-binary people (46%) reported experiencing online abuse since the beginning of COVID-19 (Glitch report, 2020). Our aim is to create 'equally safe' online spaces by prevention, intervention and support for online GBV through the development of advanced Machine Learning algorithms.

In contrast to previous research in this area, our team will include experts on GBV and online harassment to ensure that we frame the problem in a way which is most helpful to victims/survivors of GBV. In other words, we not only focus on *how* to automatically detect online abuse, but also re-think *what* it is we need to detect, how we can *support* the victims and how to *prevent* online GBV through promoting digital citizenship (i.e. prevention and intervention aimed at perpetrators and bystanders).

Our methodology is based on the Scottish Government's Equally Safe strategy and implements a Responsible Innovation Approach in a close collaboration with 3rd sector charities with a long-standing track record in this domain. Our proposal aims to create the following impacts:
1. Create longterm technical solutions to support safer online spaces, including advanced abuse detection tools, tools to automatically generate counter narratives aimed at perpetrators and bystanders, and a chatbot for providing proactive support to victims/survivors.
2. Promote 'equitable' algorithms which are able to reflect multiple perspectives/viewpoints and not marginalise minority views;
3. Increase digital literacy concerning the safe use of social media from an early age.

Publications

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