World's Best Scientists 2026 revealed!
So Young Sohn

So Young Sohn

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Social Sciences and Humanities
Korea
2026

D-Index & Metrics

Social Sciences and Humanities

D-Index
47
Citations
7986
World Ranking
3432
National Ranking
5

Engineering and Technology

D-Index
47
Citations
7792
World Ranking
4920
National Ranking
131

Research.com Recognitions

  • 2026 - Research.com Social Sciences and Humanities in Korea Leader Award

Overview

So Young Sohn is affiliated with Yonsei University in South Korea and has a research focus primarily within Business, Management, and Accounting. Their work spans several subfields including Economics and Econometrics, Management of Technology and Innovation, Strategy and Management, Accounting, and Management Information Systems.

The scientist has contributed to topics such as Intellectual Property and Patents, Innovation and Knowledge Management, Innovation Policy and R&D, Innovation Diffusion and Forecasting, FinTech, Crowdfunding, Digital Finance, Microfinance and Financial Inclusion, and Machine Learning in Materials Science.

Recent notable publications by So Young Sohn include:

  • Machine-learning-based deep semantic analysis approach for forecasting new technology convergence (2020), Technological Forecasting and Social Change
  • Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach (2020), Journal of Intelligent Manufacturing
  • Early detection of valuable patents using a deep learning model: Case of semiconductor industry (2020), Technological Forecasting and Social Change
  • Exploring new digital therapeutics technologies for psychiatric disorders using BERTopic and PatentSBERTa (2022), Technological Forecasting and Social Change
  • Graph convolutional network-based credit default prediction utilizing three types of virtual distances among borrowers (2020), Expert Systems with Applications

The scientist frequently publishes in journals such as PLoS ONE, Technological Forecasting and Social Change, Scientometrics, IEEE Transactions on Engineering Management, and Journal of Intelligent Manufacturing.

They collaborate regularly with several coauthors, including Won Kyung Lee, Su Jung Jee, Tae San Kim, Jong Wook Lee, and Hyunwoo Woo, reflecting a network of research partnerships.

Best Publications

  • Support vector machines for default prediction of SMEs based on technology credit

    Hong Sik Kim;So Young Sohn

  • Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents

    Won Sang Lee;Eun Jin Han;So Young Sohn

  • Data fusion, ensemble and clustering to improve the classification accuracy for the severity of road traffic accidents in Korea

    So Young Sohn;Sung Ho Lee

  • Structural equation model for predicting technology commercialization success index (tcsi)

    So Young Sohn;Tae Hee Moon

  • Fuzzy QFD for supply chain management with reliability consideration

    So Young Sohn;In Su Choi

  • Meta analysis of classification algorithms for pattern recognition

    So Young Sohn

  • Global stock market investment strategies based on financial network indicators using machine learning techniques

    Tae Kyun Lee;Tae Kyun Lee;Joon Hyung Cho;Deuk Sin Kwon;So Young Sohn

  • Technology credit scoring model with fuzzy logistic regression

    So Young Sohn;Dong Ha Kim;Jin Hee Yoon

  • Segmentation of stock trading customers according to potential value

    H. W. Shin;S. Y. Sohn

  • Pattern recognition for road traffic accident severity in Korea.

    So Young Sohn;Hyungwon Shin

  • A novel decomposition analysis of green patent applications for the evaluation of R&D efforts to reduce CO2 emissions from fossil fuel energy consumption

    Joon Hyung Cho;So Young Sohn

  • Beyond absorptive capacity in open innovation process: the relationships between openness, capacities and firm performance

    Joon Mo Ahn;Yonghan Ju;Tae Hee Moon;Timothy Herbert Minshall

  • Structural equation model for the evaluation of national funding on R&D project of SMEs in consideration with MBNQA criteria.

    S.Y. Sohn;Yong Gyu Joo;Hong Kyu Han

  • Decision Tree based on data envelopment analysis for effective technology commercialization

    So Young Sohn;Tae Hee Moon

  • Cluster-based dynamic scoring model

    Michael K. Lim;So Young Sohn

  • Technological convergence in standards for information and communication technologies

    Eun Jin Han;So Young Sohn

  • Machine-learning-based deep semantic analysis approach for forecasting new technology convergence

    Tae San Kim;So Young Sohn

  • Comparison of technology efficiency for CO2 emissions reduction among European countries based on DEA with decomposed factors

    Deuk Sin Kwon;Joon Hyung Cho;So Young Sohn

  • An Optimization Approach for the Placement of Bicycle-sharing stations to Reduce Short Car Trips: An Application to the City of Seoul

    Chung Park;So Young Sohn

  • Multitask learning for health condition identification and remaining useful life prediction: deep convolutional neural network approach

    Tae San Kim;So Young Sohn

  • Predicting the financial performance index of technology fund for SME using structural equation model

    So Young Sohn;Hong Sik Kim;Tae Hee Moon

  • Searching customer patterns of mobile service using clustering and quantitative association rule

    So Young Sohn;Yoonseong Kim

  • Customer pattern search for after-sales service in manufacturing

    Jin Sook Ahn;So Young Sohn

  • Structural equation model for effective CRM of digital content industry

    Yong Gyu Joo;So Young Sohn

Frequent Co-Authors

David Probert
David Probert University of Cambridge
David J. Hand
David J. Hand Imperial College London
Youngjo Lee
Youngjo Lee Seoul National University

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