書誌事項
- タイトル別名
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- Classification of Product Categories Based on Onomatopoeia Words in Product Reviews Using Cluster Analysis
説明
Nowadays, there are a number of product reviews on the Internet with the development of the consumer generated media as typified by social networking sites, blogs, and customer review sites. These reviews influence a consumer's buying decision and a company's market research. They are a lot valuable to both customers and companies, so that sentiment analysis becomes an active area of research. A sentiment polarity dictionary is essential to the sentiment analysis. We focus attention on onomatopoeia words in product reviews. It is noted that product reviews written by consumers in Japanese contain many onomatopoeia words. Japanese onomatopoeia can convey a subtle sense of features of products and customer's emotion. It is assumed that each onomatopoeia word in a product review provides a valuable clue to understanding a consumer's opinion. In this paper, we describe the appearance frequency of onomatopoeia words. After analysis of 729,865 reviews from Yahoo! Shopping, it is found that 482 words appeared in 52,121 reviews. We classify product categories in terms of the appearance frequency of onomatopoeia words with hierarchical cluster analysis and extract 978 pairs of product categories and onomatopoeia words which are likely connected to each other. Ten subjects judge the validity of these 978 pairs and consequently we conclude that 658 pairs are deemed appropriate for sentiment analysis. Further examination reveals the following two points: (1) it is highly possible that impressions of each product are described in the reviews containing onomatopoeias; and (2) the sentiment polarity of onomatopoeia differs depending on product categories.
収録刊行物
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- 人工知能学会論文誌
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人工知能学会論文誌 30 (1), 246-256, 2015
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390001205108002304
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- NII論文ID
- 130004927368
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- ISSN
- 13468030
- 13460714
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可