A word-scale probabilistic latent variable model for detecting human values

Yasuhiro Takayama, Yoichi Tomiura, Emi Ishita, Douglas W. Oard, Kenneth R. Fleischmann, An Shou Cheng

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

4 被引用数 (Scopus)

抄録

This paper describes a probabilistic latent variable model that is designed to detect human values such as justice or freedom that a writer has sought to reflect or appeal to when participating in a public debate. The proposed model treats the words in a sentence as having been chosen based on specific values; values reflected by each sentence are then estimated by aggregating values associated with each word. The model can determine the human values for the word in light of the influence of the previous word. This design choice was motivated by syntactic structures such as noun+noun, adjective+noun, and verb+adjective. The classifier based on the model was evaluated on a test collection containing 102 manually annotated documents focusing on one contentious political issue - Net neutrality, achieving the highest reported classification effectiveness for this task. We also compared our proposed classifier with human second anno-tator. As a result, the proposed classifier effectiveness is statistically comparable with human annotators.

本文言語英語
ホスト出版物のタイトルCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management
出版社Association for Computing Machinery, Inc
ページ1489-1498
ページ数10
ISBN(電子版)9781450325981
DOI
出版ステータス出版済み - 11 3 2014
イベント23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, 中国
継続期間: 11 3 201411 7 2014

出版物シリーズ

名前CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management

その他

その他23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
国/地域中国
CityShanghai
Period11/3/1411/7/14

All Science Journal Classification (ASJC) codes

  • 情報システムおよび情報管理
  • コンピュータ サイエンスの応用
  • 情報システム

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