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공공누리This item is licensed Korea Open Government License

dc.contributor.author
정병기
dc.contributor.author
윤장혁
dc.contributor.author
이재민
dc.date.accessioned
2022-03-29T01:41:01Z
dc.date.available
2022-03-29T01:41:01Z
dc.date.issued
2019-10-15
dc.identifier.issn
0268-4012
dc.identifier.uri
https://repository.kisti.re.kr/handle/10580/16582
dc.description.abstract
Social media data have recently attracted considerable attention as an emerging voice of the customer as it has rapidly become a channel for exchanging and storing customer-generated, large-scale, and unregulated voices about products. Although product planning studies using social media data have used systematic methods for product planning, their methods have limitations, such as the difficulty of identifying latent product features due to the use of only term-level analysis and insufficient consideration of opportunity potential analysis of the identified features. Therefore, an opportunity mining approach is proposed in this study to identify product opportunities based on topic modeling and sentiment analysis of social media data. For a multifunctional product, this approach can identify latent product topics discussed by product customers in social media using topic modeling, thereby quantifying the importance of each product topic. Next, the satisfaction level of each product topic is evaluated using sentiment analysis. Finally, the opportunity value and improvement direction of each product topic from a customer-centered view are identified by an opportunity algorithm based on product topics’ importance and satisfaction. We expect that our approach for product planning will contribute to the systematic identification of product opportunities from large-scale customer-generated social media data and will be used as a real-time monitoring tool for changing customer needs analysis in rapidly evolving product environments. Highlights We propose a social media mining approach for product opportunity exploration. The approach is built on topic modeling and sentiment analysis of social media data. The product opportunity consists of the importance and satisfaction of product topics. Opportunity levels and improvement directions of product topics are identified. The approach contributes to systematic product opportunity discovery from social media.
dc.language.iso
eng
dc.publisher
Elsevier
dc.relation.ispartofseries
International journal of information management;
dc.title
Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis
dc.identifier.doi
10.1016/j.ijinfomgt.2017.09.009
dc.citation.volume
48
dc.contributor.approver
KOAR, ADMIN
dc.date.dateaccepted
2022-03-29T01:41:01Z
dc.date.datesubmitted
2022-03-29T01:41:01Z
dc.identifier.bibliographicCitation
vol. 48
dc.identifier.url
https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=NART97702597
dc.subject.keyword
Product opportunity
dc.subject.keyword
New product development
dc.subject.keyword
Social media mining
dc.subject.keyword
Opportunity algorithm
dc.subject.keyword
Topic modelingSentiment analysis
Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
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