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[학술저널]

한국어 감정분석 코퍼스를 활용한 양상정보 기반의 감정분석 연구

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한국어 감정분석 코퍼스를 활용한 양상정보 기반의 감정분석 연구

Modality-based Sentiment Analysis through the Utilization of the Korean Sentiment Analysis Corpus

신효필(서울대학교) 김문형(서울대학교) 박수지(서울대학교)

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초록

This study develops a practical application of language resources from the Korean Sentiment Analysis Corpus (KOSAC) for sentiment analysis research. With this in mind, based on their sentiment properties and the probabilistic factors of annotated expressions from KOSAC, we extracted annotated expressions and refined them to be a sentiment analysis research resource. This study attempted to break away from simple calculation methods dependant on the distribution of lexical polarity items seen in previous research. Additionally, in order to perform more sophisticated sentiment analysis, we attempted to introduce pragmatic information which includes modality. In order to achieve this, we cataloged expressions that include pragmatic information related to the speaker"s attitude, based on their relative probability in KOSAC. After doing so, this study shows a practical application of this new language resource to subjectivity analysis research. When using this new resource, this research demonstrates an accuracy improvement of around 6%. This demonstrates very clearly that, in addition to polarity items, there exists a need to include a variety of aspects and lexical information when doing this type of research. Moreover, this extraction of sentiment expressions, depending on their semantic and pragmatic properties, not only shows an additional use of KOSAC, but also establishes a new resource in the field of sentiment analysis.

목차

1. 서론
2. 한국어감정분석코퍼스
3. 감정표현 추출
4. 양상정보를 이용한 감정 분석
5. 결론
참고문헌
Abstract

참고문헌(27)

  • 1.

    김문형․장하연․조유미․신효필(2013), “KOSAC(Korean Sentiment Analysis Corpus): 한국어 감정 및 의견 분석 코퍼스”, 「2013년 한국컴퓨터종합학술대회 논문 집」.

  • 2.

    Banfield, Ann (1982), Unspeakable Sentences, Boston: Routledge and Kegan Paul.

  • 3.

    Bergler, Sabine (1992), Evidential Analysis or Reported Speech, Ph.D Dissertation, Brandeis University.

  • 4.

    Chafe, Wallace & Joanna Nicholas (eds.) (1986), Evidentiality: The Linguistic Coding of Epistemology, Norwood: Ablex.

  • 5.

    Choi, Yejin, Claire Cardie, Ellen Riloff & Siddharth Patwardhan (2005), Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns, Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP 2005).

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