A Sentiment-labelled Corpus of Hansard Parliamentary Debate Speeches

author: Gavin Abercrombie, School of Computer Science, University of Manchester
published: May 30, 2018,   recorded: May 2018,   views: 3
released under terms of: Creative Commons Attribution (CC-BY)
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Hansard transcripts provide access to the opinions of MPs on many important issues, but are rather difficult for people to effectively process. Existing corpora for sentiment analysis in Hansard debates rely on speakers' votes as sentiment polarity labels, but these votes are known to be constrained by speakers' party affiliations. Over two rounds of manual annotation, we develop an annotation scheme and create a novel corpus designed for use in the evaluation of automatic sentiment analysis systems using both automatically and manually applied speech sentiment polarity class labels. Following observations of the effects on speech sentiment of differing sentiment polarities in debate motions (proposals), we also apply sentiment labels to the debate motions. We find that humans are able to reach high agreement in identifying sentiment polarity in these debates, and also that manually applied and automatically retrieved class labels differ somewhat, suggesting that speech content does not always reflect the voting behaviour of Members of the Parliament.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: