著者
井上 祐輔 竹岡 志朗 高木 修一
出版者
日本情報経営学会
雑誌
日本情報経営学会誌 (ISSN:18822614)
巻号頁・発行日
vol.35, no.1, pp.59-71, 2014-09-30

This article discusses some methodological considerations about using Text Mining technology. We interpret the result of Text Mining, based on New Institutional Theory. As a result, we made clear that sign representation is the leverage point in an understanding either isomorphism or differentiation. Moreover, we designate the diffusion of innovations as to be common sign representations. Finally, we suggest the method of Text Mining as how to analyze the diffusion process.
著者
竹岡 志朗 高木 修一 井上 祐輔
出版者
日本情報経営学会
雑誌
日本情報経営学会誌 (ISSN:18822614)
巻号頁・発行日
vol.35, no.1, pp.72-86, 2014-09-30

This article examines the diffusion of innovations that resulted in micro social phenomena. We use text mining to analyze online bulletin boards (kakaku.com). Lastly, we discuss an analytical method that can support decision-making in new-product development, and explore the needs of word-of-mouth data on the Internet, such as blogs and social networking sites (SNS).
著者
竹岡 志朗 高木 修一 井上 祐輔
出版者
日本情報経営学会
雑誌
日本情報経営学会誌 (ISSN:18822614)
巻号頁・発行日
vol.35, no.1, pp.72-86, 2014

This article examines the diffusion of innovations that resulted in micro social phenomena. We use text mining to analyze online bulletin boards (kakaku.com). Lastly, we discuss an analytical method that can support decision-making in new-product development, and explore the needs of word-of-mouth data on the Internet, such as blogs and social networking sites (SNS).
著者
井上 祐輔 竹岡 志朗 高木 修一
出版者
日本情報経営学会
雑誌
日本情報経営学会誌 (ISSN:18822614)
巻号頁・発行日
vol.35, no.1, pp.59-71, 2014

This article discusses some methodological considerations about using Text Mining technology. We interpret the result of Text Mining, based on New Institutional Theory. As a result, we made clear that sign representation is the leverage point in an understanding either isomorphism or differentiation. Moreover, we designate the diffusion of innovations as to be common sign representations. Finally, we suggest the method of Text Mining as how to analyze the diffusion process.