What Determines an Agreeable and Adoptable Idea? A Study of User Ideas on MyStarbucksIdea.com. - Hanjun Lee; Soyoung Seo (HICSS, 2013)

The More the Worse? Mining Valuable Ideas with Sentiment Analysis for Idea Recommendation. - Hanjun Lee; Keunho Choi; Donghee Yoo; Yongmoo Suh; Guijia He; Soowon Lee (PACIS, 2013)

The Influence of Negative Emotions in an Online Brand Community on Customer Innovation Activities. - Hanjun Lee; Suyeon Jeong; Yongmoo Suh (HICSS, 2014)

Gift or threat? An examination of voice of the customer: The case of MyStarbucksIdea.com. - Hanjun Lee; Jinyoung Han; Yongmoo Suh (Electron. Commer. Res. Appl., 2014)

An Ontology-based Co-creation Enhancing System for Idea Recommendation in an Online Community. - Donghee Yoo; Keunho Choi; Hanjun Lee; Yongmoo Suh (Data Base, 2015)

7.1 256Gb 3b/cell V-NAND flash memory with 48 stacked WL layers. - Dongku Kang; Woopyo Jeong; Chulbum Kim; Doo-Hyun Kim; Yong-Sung Cho; Kyung-Tae Kang; Jinho Ryu; Kyung-Min Kang; Sungyeon Lee; Wandong Kim; Hanjun Lee; Jaedoeg Yu; et al. (ISSCC, 2016)

Who creates value in a user innovation community? A case study of MyStarbucksIdea.com. - Hanjun Lee; Yongmoo Suh (Online Inf. Rev., 2016)

The Influence of Negative Emotions on Customer Innovation Activities: An Examination Using Sentiment Analysis. - Hanjun Lee; Suyeon Jeong; Yongmoo Suh (Data Base, 2017)

256 Gb 3 b/Cell V-nand Flash Memory With 48 Stacked WL Layers. - Dongku Kang; Woopyo Jeong; Chulbum Kim; Doo-Hyun Kim; Yong-Sung Cho; Kyung-Tae Kang; Jinho Ryu; Kyung-Min Kang; Sungyeon Lee; Wandong Kim; Hanjun Lee; Jaedoeg Yu; et al. (IEEE J. Solid State Circuits, 2017)

A Predictive Model for Forecasting Spare Parts Demand in Military Logistics. - Hanjun Lee; Jaedong Kim (IEEM, 2018)

A 1Tb 4b/cell 64-stacked-WL 3D NAND flash memory with 12MB/s program throughput. - Seungjae Lee 001; Chulbum Kim; Minsu Kim 004; Sung-Min Joe; Joonsuc Jang; Seungbum Kim; Kangbin Lee; Jisu Kim; Jiyoon Park; Hanjun Lee; Min-Seok Kim; Seonyong Lee; et al. (ISSCC, 2018)

Recommending valuable ideas in an open innovation community: A text mining approach to information overload problem. - Hanjun Lee; Keunho Choi; Donghee Yoo; Yongmoo Suh; Soowon Lee; Guijia He (Ind. Manag. Data Syst., 2018)

13.1 A 1Tb 4b/cell NAND Flash Memory with tPROG=2ms, tR=110µs and 1.2Gb/s High-Speed IO Rate. - Doo-Hyun Kim; Hyunggon Kim; Sung-Won Yun; Youngsun Song; Jisu Kim; Sung-Min Joe; Kyung-Hwa Kang; Joonsuc Jang; Hyun-Jun Yoon; Kangbin Lee; Minseok Kim; Joonsoo Kwon; et al. (ISSCC, 2020)

Two faces of review inconsistency: The respective effects of internal and external inconsistencies on job review helpfulness. - Jinwook Choi; Seung Hee Yoo; Hanjun Lee (Comput. Hum. Behav., 2023)

Mining the determinants of review helpfulness: a novel approach using intelligent feature engineering and explainable AI. - Jiho Kim; Hanjun Lee; Hongchul Lee (Data Technol. Appl., 2023)

Factors influencing attitude toward advertisements in location-based services and the mediation effect of advertisement context value. - Seokho Victor Lee; Hyungjin Lukas Kim; Kihyon Kim; Jinyoung Han; Hanjun Lee (Int. J. Mob. Commun., 2024)

30.1 A 28Gb/mm24XX-Layer 1Tb 3b/Cell WF-Bonding 3D-NAND Flash with 5.6Gb/s/Pin IOs. - Sang-Soo Park; Jaedoeg Lyu; Myungjun Kim; Jaeyun Lee; Youngsun Song; Chungho Yu; Makoto Hirano; Yongseok Kwon; Jonghoon Park; Hojoon Kim; Daein Lee; Donghyun Seo; et al. (ISSCC, 2025)

Predicting Job Review Helpfulness: Machine Learning and SHAP Approach. - Ziyi Wang; Hanjun Lee (PACIS, 2025)

Roles of topic features in perceived helpfulness of online company reviews. - Jiho Kim; Hongchul Lee; Hanjun Lee (Data Technol. Appl., 2025)