Policy-focused Stance Detection in Parliamentary Debate Speeches
Legislative debate transcripts provide citizens with information about the activities of their elected representatives, but are difficult for people to process. We propose the novel task of policy-focused stance detection, in which both the policy proposals under debate and the position of the spea...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Linköping University Electronic Press
2022-07-01
|
| Series: | Northern European Journal of Language Technology |
| Online Access: | https://nejlt.ep.liu.se/article/view/3454 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832591270809174016 |
|---|---|
| author | Gavin Abercrombie Riza Batista-Navarro |
| author_facet | Gavin Abercrombie Riza Batista-Navarro |
| author_sort | Gavin Abercrombie |
| collection | DOAJ |
| description |
Legislative debate transcripts provide citizens with information about the activities of their elected representatives, but are difficult for people to process. We propose the novel task of policy-focused stance detection, in which both the policy proposals under debate and the position of the speakers towards those proposals are identified. We adapt a previously existing dataset to include manual annotations of policy preferences, an established schema from political science. We evaluate a range of approaches to the automatic classification of policy preferences and speech sentiment polarity, including transformer-based text representations and a multi-task learning paradigm. We find that it is possible to identify the policies under discussion using features derived from the speeches, and that incorporating motion-dependent debate modelling, previously used to classify speech sentiment, also improves performance in the classification of policy preferences. We analyse the output of the best performing system, finding that discriminating features for the task are highly domain-specific, and that speeches that address policy preferences proposed by members of the same party can be among the most difficult to predict.
|
| format | Article |
| id | doaj-art-e2c2037a4ab34acdb180e90fb71ac197 |
| institution | Kabale University |
| issn | 2000-1533 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | Linköping University Electronic Press |
| record_format | Article |
| series | Northern European Journal of Language Technology |
| spelling | doaj-art-e2c2037a4ab34acdb180e90fb71ac1972025-01-22T15:25:32ZengLinköping University Electronic PressNorthern European Journal of Language Technology2000-15332022-07-018110.3384/nejlt.2000-1533.2022.3454Policy-focused Stance Detection in Parliamentary Debate SpeechesGavin Abercrombie0Riza Batista-Navarro1University of ManchesterUniversity of Manchester Legislative debate transcripts provide citizens with information about the activities of their elected representatives, but are difficult for people to process. We propose the novel task of policy-focused stance detection, in which both the policy proposals under debate and the position of the speakers towards those proposals are identified. We adapt a previously existing dataset to include manual annotations of policy preferences, an established schema from political science. We evaluate a range of approaches to the automatic classification of policy preferences and speech sentiment polarity, including transformer-based text representations and a multi-task learning paradigm. We find that it is possible to identify the policies under discussion using features derived from the speeches, and that incorporating motion-dependent debate modelling, previously used to classify speech sentiment, also improves performance in the classification of policy preferences. We analyse the output of the best performing system, finding that discriminating features for the task are highly domain-specific, and that speeches that address policy preferences proposed by members of the same party can be among the most difficult to predict. https://nejlt.ep.liu.se/article/view/3454 |
| spellingShingle | Gavin Abercrombie Riza Batista-Navarro Policy-focused Stance Detection in Parliamentary Debate Speeches Northern European Journal of Language Technology |
| title | Policy-focused Stance Detection in Parliamentary Debate Speeches |
| title_full | Policy-focused Stance Detection in Parliamentary Debate Speeches |
| title_fullStr | Policy-focused Stance Detection in Parliamentary Debate Speeches |
| title_full_unstemmed | Policy-focused Stance Detection in Parliamentary Debate Speeches |
| title_short | Policy-focused Stance Detection in Parliamentary Debate Speeches |
| title_sort | policy focused stance detection in parliamentary debate speeches |
| url | https://nejlt.ep.liu.se/article/view/3454 |
| work_keys_str_mv | AT gavinabercrombie policyfocusedstancedetectioninparliamentarydebatespeeches AT rizabatistanavarro policyfocusedstancedetectioninparliamentarydebatespeeches |