Cyber Violence Against Women and Girls: Leveraging AI to Evaluate Impact by Social Media Platforms Aston University in United Kingdom

Department: College of Business and Social Sciences

Contract Type: Fixed Term

Basis: Full Time

Closing Date: Thursday 24 ^th April 2025 23.59 (UK time)

Supervisor: Dr Anitha Chinnaswamy & Dr Kanimozhi Narayanan

Applications are invited for a three-year PhD studentship, supported by the College of Business and Social Sciences to be undertaken within Aston Business School at Aston University.

The position is available to start in October 2025.

Financial Support

This studentship includes a bursary to cover the tuition fees and an annual maintenance allowance for living costs.

Background to the Project

This study examines the role of artificial intelligence (AI) in mitigating and inadvertently perpetuating Cyber Violence Against Women and Girls (CVAWG) on social media platforms like Facebook, Instagram, Twitter, and TikTok. While AI tools, such as automated content moderation and hate speech detection, are increasingly used to address cyber violence, they also present significant challenges and unintended consequences. The focus of this research is to understand how AI can be more effective in combating cyber violence, especially CVAWG, without exacerbating inequalities or creating new forms of harm.

CVAWG includes a range of harmful behaviours, such as online harassment, doxxing, non-consensual sharing of intimate images, and gender-based hate speech. Studies show that women are disproportionately affected, being 27 times more likely to be harassed online than men, with platforms often enabling abuse rather than providing safe spaces for users (UN Women, 2021). AI algorithms on social media platforms have been introduced to identify and remove abusive content. These algorithms, which rely on machine learning models and natural language processing (NLP) to detect signs of harassment, aim to address online violence. However, these technologies face limitations in their effectiveness

A key challenge with AI in content moderation is its inability to fully contextualise abusive behaviour. For instance, legitimate forms of activism or satire may be misclassified as harmful, leading to gaps in intervention (Gongane et al., 2022). Furthermore, biases inherent in AI algorithms can perpetuate discriminatory practices, particularly against marginalised women who experience intersectional forms of violence (Noble, 2018). This highlights the dual role of AI - while it has the potential to mitigate CVAWG, it can also inadvertently contribute to harm.

This research will use the socio-technical systems (STS) framework for analysis, STS theory posits that the technical components of systems (like AI tools) and social dimensions (such as user behaviour, existing policies, and cultural contexts) are interdependent, and both need to be understood to address societal challenges (see Wu et al., 2015). By applying this framework, the study will examine how AI tools operate within social media platforms and how they can be improved to effectively combat CVAWG to mitigate existing societal inequities.

To address the research questions, the study will employ a mixed-methods approach that includes computational content analysis, case studies and qualitative interviews. First, content analysis will be used to evaluate the efficiency and accuracy of AI algorithms in detecting cyber violence, specifically focusing on how well AI can contextualize abusive behaviour. Additionally, case studies of specific incidents will be conducted to understand how AI tools either succeeded or failed in addressing cyber violence. This will involve analysing machine learning tools such as NLP and cluster analysis to identify errors in content classification and trends in algorithmic limitations.

Second, qualitative interviews will be conducted with platform moderators, victims of cyber violence, and AI developers. These interviews will explore the psychological and technological impacts of AI, focusing on biases, inconsistencies, and gaps in AI’s role in reducing cyber violence. Thematic analysis will be used to identify recurring themes via the lived experiences of different stakeholders navigating online abuse.

This study will contribute to interdisciplinary discussions on gender, technology, and online safety. It will offer practical insights for tech companies and policymakers to better understand the role of AI tools in moderating cyber violence and provide recommendations to improve the effectiveness of AI tools and its role against CVAWG. The research will aim to ensure that AI tools are both technically effective and socially responsible in reducing CVAWG.

Person Specification

The successful candidate should hold a Masters degree in the social sciences (or related disciplines) with a Merit overall (or equivalent) with a dissertation/research element, PLUS a First or Upper Second Class Honours degree (or an equivalent qualification from an overseas institution).

Contact information

For formal enquiries about this project please contact Dr Anitha Chinnaswamy [email protected] .

Submitting an application

Your application must include:

1. English language copies of the transcripts and certificates for all your higher education degrees, including any Bachelor degrees.
2. A Research Proposal Statement detailing your understanding of the research area, how you would approach the project, and a brief review of relevant literature. Be sure to use the title of the research project you are applying for. There is no set format or word count.
3. A personal statement which outlines any further information which you think is relevant to your application, such as your personal suitability for research, career aspirations, possible future research interests, and further description of relevant employment experience.
4. Two academic referees who can discuss your suitability for independent research. References must be on headed paper, signed and dated no more than 2 years old. At least one reference should be from your most recent University. You can submit your references at a later date if necessary.
5. Evidence that you meet the English Language requirements . If you do not currently meet the language requirements, you can submit this at a later stage.
6. A copy of your passport . Where relevant, include evidence of settled or pre-settled status.

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If you require further information about the application process, please contact the Postgraduate Admissions team at [email protected]