Project code



School of Computing

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3 year full-time or 6 year part-time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Alaa Mohasseb from the School of Computing and Dr Alessia Tranchese from the School of Education, Languages and Linguistics.

The work on this project could involve:

  • Explore and investigate different NLP and machine learning methods to improve the identification of online misogyny.
  • Data collection and pre-processing.
  • Identify patterns and trends within the collected dataset.
  • Conduct sentiment analysis to understand the emotional tone and nuances in online misogynistic content.


The pervasive nature of online misogyny has become a serious concern in the digital age, highlighting the need for comprehensive studies that employ advanced technologies to analyze and understand its patterns and impact. This project aims to leverage artificial intelligence (AI) to delve into the intricate nuances of online misogynistic behaviour, unveiling underlying patterns and shedding light on the profound implications it has on individuals and society.

The objective of this project is to employ state-of-the-art Natural Language Processing (NLP) techniques to systematically analyze instances of online misogyny across various platforms. By using Machine learning algorithms, to identify recurring patterns, linguistic markers, and contextual triggers that contribute to the prevalence of misogynistic content. Additionally, the project seeks to quantify the impact of such content on the well-being of individuals, fostering a deeper understanding of the societal consequences of online misogyny.

The Project will also involve the development of a robust AI model trained on a diverse dataset of online communication, specifically focusing on instances of misogynistic language. The model will employ machine learning techniques to recognize patterns, discern context, and categorize different forms of online misogyny. Furthermore, the project will explore the intersectionality of online misogyny, considering factors such as race, ethnicity, and sexual orientation. By doing so, we aim to provide a comprehensive understanding of how various dimensions of identity intersect with online misogynistic behaviour.

The insights gained from this project have the potential to inform the development of more effective moderation tools, policies, and educational initiatives. Furthermore, understanding the patterns and impact of online misogyny can contribute to fostering a safer digital environment for all users.


Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only. 

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (conditions apply).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

The entry requirements for a PhD or MPhil include an upper second class honours degree or equivalent in a relevant subject or a master's degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. All applicants are subject to interview.

If English is not your first language, you'll need English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

If you don't meet the English language requirements yet, you can achieve the level you need by successfully completing a pre-sessional English programme before you start your course.

Good experience in the fundamentals of Natural Language Processing, Data Analytics and Machine Learning techniques, preferably good technical skills in text processing. Competent in applying NLP toolkits, such as NLTK or Spacy, or ML toolkits such as Scikit-Learn or Tensorflow. 

Good programming skills in Python, analytical skills, and knowledge of foundations of computer science are also required. You should be able to think independently, including the formulation of research problems and have strong oral and written communication skills and good time management.


How to apply

We’d encourage you to contact Dr Alaa Mohaseb  ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code: COMP6431025