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Automatically annotating a five-billion-word corpus of Japanese blogs for sentiment and affect analysis


Automatically annotating a five-billion-word corpus of japanese blogs for affect and sentiment analysis.pdf1.51 MBPDF見る/開く

タイトル: Automatically annotating a five-billion-word corpus of Japanese blogs for sentiment and affect analysis
著者: Ptaszynski, Michal 著作を一覧する
Rzepka, Rafal 著作を一覧する
Araki, Kenji 著作を一覧する
Momouchi, Yoshio 著作を一覧する
発行日: 2014年 1月
出版者: Elsevier
誌名: Computer Speech & Language
巻: 28
号: 1
開始ページ: 38
終了ページ: 55
出版社 DOI: 10.1016/j.csl.2013.04.010
抄録: This paper presents our research on automaticannotation of a five-billion-word corpus ofJapanese blogs with information on affect andsentiment. We first perform a study in emotionblog corpora to discover that there has beenno large scale emotion corpus available forthe Japanese language. We choose the largestblog corpus for the language and annotate itwith the use of two systems for affect analysis:ML-Ask for word- and sentence-levelaffect analysis and CAO for detailed analysisof emoticons. The annotated informationincludes affective features like sentencesubjectivity (emotive/non-emotive) or emotionclasses (joy, sadness, etc.), useful in affectanalysis. The annotations are also generalizedon a 2-dimensional model of affect to obtaininformation on sentence valence/polarity(positive/negative) useful in sentiment analysis.The annotations are evaluated in severalways. Firstly, on a test set of a thousand sentencesextracted randomly and evaluated byover forty respondents. Secondly, the statisticsof annotations are compared to other existingemotion blog corpora. Finally, the corpus isapplied in several tasks, such as generation ofemotion object ontology or retrieval of emotionaland moral consequences of actions.
Rights: © 2014, Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
資料タイプ: article (author version)
出現コレクション:雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

提供者: Rafal Rzepka


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