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<Paper uid="P06-2079">
  <Title>Examining the Role of Linguistic Knowledge Sources in the Automatic Identification and Classification of Reviews</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> This paper examines two problems in document-level sentiment analysis: (1) determining whether a given document is a review or not, and (2) classifying the polarity of a review as positive or negative.</Paragraph>
    <Paragraph position="1"> We first demonstrate that review identification can be performed with high accuracy using only unigrams as features. We then examine the role of four types of simple linguistic knowledge sources in a polarity classification system.</Paragraph>
  </Section>
class="xml-element"></Paper>