Find a postgraduate research project in your area of interest by exploring the research projects that we offer in the School of Computer Science.
We have a broad range of research projects for which we are seeking doctoral students. Browse the list of projects on this page or follow the links below to find information on doctoral training opportunities, or applying for a postgraduate research programme.
Alternatively, if you would like to propose your own project then please include a research project proposal and the name of a possible supervisor with your application.
Topic-centric sentiment analysis of UK parliamentary debates
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Other projects with the same supervisor
- Directly Funded Project (European/UK Students Only)
This research project has funding attached. Funding for this project is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.
Sentiment analysis, also known as opinion mining, is a natural language processing (NLP) task dealing with the automatic classification of text according to its conveyed sentiment. It is typically focussed on the identification of the overall sentiment---any of positive, negative or neutral---that is expressed in textual passages such as social media posts (e.g., Tweets) and online product reviews. This project is aimed at the development of approaches for a more targeted type of sentiment analysis: the identification of sentiment towards a particular subject matter, rather than just detecting overall sentiment (i.e., regardless of topic), from political discourse.
As part of this work, the PhD student will investigate and develop methods for: (1) topic detection, in which the topics being discussed in a given piece of text are identified; and (2) topic-centric sentiment analysis, which involves the analysis of sentiments specific to the automatically detected topics. The methods will be applied to the analysis of documents in the UK Hansard archives, which contain historical textual records of parliamentary debates and written statements.