Transfer learning for topic labeling: Analysis of the UK House of Commons speeches 1935–2014
Topic models are widely used in natural language processing, allowing researchers to estimate the underlying themes in a collection of documents. Most topic models require the additional step of attaching meaningful labels to estimated topics, a process that is not scalable, suffers from human bias,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2021-06-01
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| Series: | Research & Politics |
| Online Access: | https://doi.org/10.1177/20531680211022206 |