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Adjectives as indicators of subjectivity in documents

  • Robert Rittman
  • , Nina Wacholder
  • , Paul Kantor
  • , Kwong Bor Ng
  • , Tomek Strzalkowski
  • , Ying Sun
  • Rutgers - The State University of New Jersey, New Brunswick
  • City University of New York
  • SUNY Albany

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The goal of this research is to automatically predict human judgments of document qualities such as subjectivity, verbosity and depth. In this paper, we explore the behavior of adjectives as indicators of subjectivity in documents. Specifically, we test whether a subset of automatically derived subjective adjectives (Wiebe, 2000b), selected a priori, behaves differently than other adjectives. 3,200 documents were ranked by 100 subjects as being high or low in nine document qualities (Tang, Ng, Strzalkowski, & Kantor, 2003). We report a statistically significant correlation between the occurrence of adjectives in documents and human judgments of subjectivity. More importantly, we find that the subset of subjective adjectives is more strongly correlated with subjectivity than adjectives in general. These results can be used to identify document qualities for use in information retrieval and question-answering systems.

Original languageEnglish
Pages (from-to)349-359
Number of pages11
JournalProceedings of the ASIST Annual Meeting
Volume41
DOIs
StatePublished - Nov 2004

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