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 language | English |
|---|---|
| Publication status | Published - 2012 |
| Event | Workshop on Computational Approaches to Subjectivity and Sentiment Analysis - Seogwipo, Korea, Republic of Duration: 12 Jul 2012 → 12 Jul 2012 |
Workshop
| Workshop | Workshop on Computational Approaches to Subjectivity and Sentiment Analysis |
|---|---|
| Abbreviated title | WASSA |
| Country/Territory | Korea, Republic of |
| City | Seogwipo |
| Period | 12/07/12 → 12/07/12 |