dc.contributor.author | Hayes, Kieron | |
dc.date.accessioned | 2022-06-20T09:04:09Z | |
dc.date.available | 2022-06-20T09:04:09Z | |
dc.date.issued | 2022-06-20 | |
dc.identifier.uri | https://hdl.handle.net/2077/72135 | |
dc.description.abstract | Sentiment analysis is an on-going field of research within the realm of Natural Language
Processing, in which we wish to accurately assess the sentiment of an author
on a given topic. Within this thesis project I construct a rule-based system for sentiment
analysis specific to the domain of hard rock and heavy metal music album
reviews. I then compare it to the performance of other approaches to the task, such
as the use of a neural network, and analyse the strengths and weaknesses of these
differing approaches. Ultimately the neural network, with sufficient training, produces
the best results for this task, and I go on to outline possible improvements that
could be made to the rule-based system in further efforts to maximise its potential. | en_US |
dc.language.iso | eng | en_US |
dc.subject | Sentiment analysis | en_US |
dc.subject | BERT | en_US |
dc.subject | Rule-based | en_US |
dc.subject | Domain-specific | en_US |
dc.subject | SentiWordNet | en_US |
dc.title | Comparative Evaluation of Sentiment Analysis Methods | en_US |
dc.type | text | |
dc.setspec.uppsok | Technology | |
dc.type.uppsok | H2 | |
dc.contributor.department | Göteborgs universitet/Institutionen för data- och informationsteknik | swe |
dc.contributor.department | University of Gothenburg/Department of Computer Science and Engineering | eng |
dc.type.degree | Student essay | |