Identification of time-evolving product opportunities via social media mining

Jaewoong Choi, Seunghyun Oh, Janghyeok Yoon, Jae-Min Lee and Byoung-Youl Coh

Technological Forecasting and Social Change, 2020, vol. 156, issue C

Abstract: This study suggests a social media mining approach for identifying time-evolving product opportunities for product improvement, customer complaint management, and competitive intelligence via event detection and tracking (EDT) and sentiment analysis. This approach applies an aging theory-based EDT algorithm to online product reviews to detect the creation of customer-stated events as groups of similar reviews and track their growth and extinction. Next, the approach uses sentiment analysis and an opportunity algorithm to evaluate time-evolving events and provides quantified clues regarding product-development directions based on events with high opportunity. To show the workings of the proposed approach, a case study involving smart speakers is presented. We expect that the approach will contribute to identifying time-evolving product opportunities from large-scale social-media data in addition to enabling the real-time monitoring of customer needs in rapidly evolving product environments.

Keywords: Product opportunity; Social media; Event detection and tracking; Voice of customer; Sentiment analysis; Product planning (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:156:y:2020:i:c:s0040162519321043

DOI: 10.1016/j.techfore.2020.120045

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