AI and Data Science for Electoral Integrity and Democratic Governance

About the Project

Project Description

Aims and Methods

This thesis develops and evaluates AI- and data science–based tools to protect electoral integrity and the free formation of voters’ will from algorithmic manipulation. It targets emerging threats such as deepfakes, coordinated disinformation, bot-driven polarisation, and algorithmic amplification across social and digital media. The project applies a computational social science approach that combines (i) machine learning and anomaly detection to identify abnormal activity patterns and coordinated behaviour, (ii) social network analysis to map actors, communities, and diffusion pathways, and (iii) multimodal and multilingual fact-checking pipelines to assess claims and detect manipulated audio/visual content.

A central objective is to build explainable and auditable detection and monitoring prototypes that support democratic accountability rather than opaque surveillance. The work integrates ethical, legal, and technical considerations throughout the lifecycle: dataset governance, bias and harm assessment, transparency of model decisions, and safeguards for fundamental rights. Evaluation will include performance metrics (precision/recall, robustness to adversarial tactics), interpretability audits, and impact-oriented analyses that relate detected manipulations to shifts in narratives, trust signals, and engagement dynamics during electoral periods.

Deliverables (indicative)

• A reproducible data pipeline for collecting, documenting, and analysing electoral-period signals from social media, online news archives, and open government datasets (e.g., procurement and political finance).
• Detection models and algorithms for coordinated disinformation, bot activity, deepfakes, and algorithmic amplification, with multilingual support.
• An explainable alerting and visualisation dashboard for monitoring campaigns, diffusion patterns, and risk indicators (for authorities, journalists, and citizens).
• An evaluation framework and ethical auditing toolkit (bias, transparency, proportionality, privacy-preserving analysis), including model cards/datasheets.
• Case studies on one or more election contexts, with a comparative analysis of tactics, actors, and narrative dynamics.

Keywords

electoral integrity; algorithmic manipulation; disinformation; deepfakes; computational social science; social network analysis; anomaly detection; multimodal fact-checking; explainable AI; AI ethics; algorithmic governance; democratic resilience; data visualisation.

How to Apply

This project is accepting applications all year round, for self-funded candidates.

Mode of Study: Full-time or part-time

Please submit your application via Computer Science and Informatics - Study - Cardiff University

In the funding field of your application, indicate “I am applying for a self-funded PhD in Computer Science and Informatics”, and specify the project title and supervisors of this project in the text box provided.

Academic criteria: A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject. Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas.

Applicants must demonstrate English language proficiency. Students who do not have English as a first language must prove this by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component. A full list of accepted qualifications is available here: https://www.cardiff.ac.uk/study/international/english-language-requirements/postgraduate

If you are interested, please contact Dr Carla Perez Almendros (perezalmendrosc@cardiff.ac.uk) sending your CV in the first instance. The application process requires you to develop an individual research proposal jointly with the supervision team, which builds on the information provided in this advert.

Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below.

Please submit your application via Computer Science and Informatics - Study - Cardiff University

In order to be considered candidates must submit the following information:

• In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal. Your research proposal should not exceed 2000 words, including references and bibliography.
• A personal statement (as part of the university application form, or as a separate attachment, if you prefer).
• A CV. Guidance on CVs for a PhD position can be found on the FindAPhD website.
• Qualification certificates and Transcripts - original and English translation, if applicable.
• References x 2 which should be academic references. Please note you need to provide the reference documents as part of your application.
• Proof of English language (if applicable).

Interview– If the application meets all of the entrance requirements listed above, you will be invited to an interview.

Funding Notes

This project is offered for self-funded students only, or those with their own sponsorship or scholarship award. Where applicable, candidates will be required to cover the cost of a student visa, the healthcare surcharge, and any other costs of moving to the UK to study. These costs will not be covered by the School of Computer Science and Informatics.