Study level

PhD

Master of Philosophy

Honours

Vacation research experience scheme

Faculty/School

Science and Engineering Faculty

School of Information Systems

Topic status

We're looking for students to study this topic.

Supervisors

Dr Andrew Gibson
Position
Lecturer in Information Science
Division / Faculty
Science and Engineering Faculty

Overview

Sentiment analysis has become a highly valued form of text analysis, particularly for companies who want to distil customer sentiment from social media. As a result, it is an active area of Natural Language Processing (NLP) research. However, much of the work is concerned with the accuracy of positive and negative classification. When it comes to more nuanced analysis of affect and emotion, the research is much more limited.

This project will focus on developing approaches to nuanced analysis of affect in reflective text (where people write about themselves and their experiences). It will involve drawing upon current psychological theories of emotion and affect, and bringing them together with novel applied NLP approaches to text analysis by utilising the current state of the art in NLP.

Research activities

The project will involve:

  • identifying relevant theories of emotion and affect from the fields of cognitive science, psychology, and social psychology
  • identifying core NLP technologies that could be adapted for fine-grained affect analysis
  • developing a practical framework that synthesises theory and available technologies
  • developing software that can analyse text in line with the framework.

Outcomes

We expect the outcomes of this project to include:

  • an understanding of how contemporary theories of emotion and affect can be brought together with current NLP technologies to perform computational analysis of affect in reflective text
  • knowledge of how to effectively implement an affect analysis framework in software.

Skills and experience

To successfully complete this project, you will need to have:

  • strong programming skills in a language such as Scala, Java or Python
  • good general knowledge of NLP and text analysis
  • a strong interest in bringing theory together with application in a socio-technical way.

Scholarships

You may be able to apply for a research scholarship in our annual scholarship round.

Annual scholarship round

Keywords

Contact

Contact the supervisor for more information.