Cross-discourse Development of Supervised Sentiment Analysis in the Clinical Domain

Phillip Smith, M. Lee

Research output: Contribution to conferencePaper

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Abstract

Current approaches to sentiment analysis assume that the sole discourse function of sentiment-bearing texts is expressivity. However, the persuasive discourse function also utilises expressive language. In this work, we present the results of training supervised classifiers on a new corpus of clinical texts that contain documents with an expressive discourse function, and we test the learned models on a subset of the same corpus containing persuasive texts. The results of this indicate that despite the difference in discourse function, the learned models perform favourably.
Original languageEnglish
Publication statusPublished - 2012
EventWorkshop on Computational Approaches to Subjectivity and Sentiment Analysis - Seogwipo, Korea, Republic of
Duration: 12 Jul 201212 Jul 2012

Workshop

WorkshopWorkshop on Computational Approaches to Subjectivity and Sentiment Analysis
Abbreviated titleWASSA
CountryKorea, Republic of
CitySeogwipo
Period12/07/1212/07/12

Bibliographical note

The full text is available from: http://aclweb.org/anthology/W/W12/W12-3712.pdf

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