期刊名称：Conference on European Chapter of the Association for Computational Linguistics (EACL)
出版年度：2010
卷号：2010
出版社：ACL Anthology
摘要：One of the central challenges in sentimentbased
text categorization is that not every
portion of a document is equally informative
for inferring the overall sentiment
of the document. Previous research
has shown that enriching the sentiment labels
with human annotators¡¯ ¡°rationales¡±
can produce substantial improvements in
categorization performance (Zaidan et al.,
2007). We explore methods to auto-
matically generate annotator rationales for
document-level sentiment classification.
Rather unexpectedly, we find the automatically
generated rationales just as helpful
as human rationales.
