Tech Reports

ULCS-14-002

Predicting speaker attitude in the UK House of Commons

Zaher Salah, Frans Coenen and Davide Grossi

Abstract

In this paper the authors seek to establish the most appropriate mechanism for conducting sentiment analysis with respect to political debates so as to predict their outcome. To this end two alternative approaches are considered, the classification based approach and the lexicon based approach. In the context of the second approach either generic or domain specific lexicons may be adopted, both options are compared with the classification based approach. The comparison between the potential sentiment mining approaches and supporting techniques is conducted by predicting the attitude of individual debaters (speakers) in political debates (using debate transcripts taken from the proceedings of the UK House of Commons). The reported comparison indicates that the attitude of speakers can be effectively predicted using sentiment mining. The authors then go on to consider whether speaker political party affiliation is a better indicator of attitude than the content of the concatenated speeches of individual debaters.

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