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http://dx.doi.org/10.11627/jkise.2019.42.1.074

Identifying Interdisciplinary Trends of Humanities, Sociology, Science and Technology Research in Korea Using Topic Modeling and Network Analysis  

Choi, Jaewoong (Department of Industrial Engineering, Konkuk University)
Jang, Jaehyuk (Department of Industrial Engineering, Konkuk University)
Kim, Dae Hwan (National Research Foundation of Korea)
Yoon, Janghyeok (Department of Industrial Engineering, Konkuk University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.42, no.1, 2019 , pp. 74-86 More about this Journal
Abstract
As many existing research fields are matured academically, researchers have encountered numbers of academic, social and other problems that cannot be addressed by internal knowledge and methodologies of existing disciplines. Earlier, pioneers of researchers thus are following a new paradigm that breaks the boundaries between the prior disciplines, fuses them and seeks new approaches. Moreover, developed countries including Korea are actively supporting and fostering the convergence research at the national level. Nevertheless, there is insufficient research to analyze convergence trends in national R&D support projects and what kind of content the projects mainly deal with. This study, therefore, collected and preprocessed the research proposal data of National Research Foundation of Korea, transforming the proposal documents to term-frequency matrices. Based on the matrices, this study derived detailed research topics through Latent Dirichlet Allocation, a kind of topic modeling algorithm. Next, this study identified the research topics each proposal mainly deals with, visualized the convergence relationships, and quantitatively analyze them. Specifically, this study analyzed the centralities of the detailed research topics to derive clues about the convergence of the near future, in addition to visualizing the convergence relationship and analyzing time-varying number of research proposals per each topic. The results of this study can provide specific insights on the research direction to researchers and monitor domestic convergence R&D trends by year.
Keywords
Convergence Research; Research Proposal; Text Mining; Topic Modeling; Network Analysis;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Blei, D. and Lafferty, J., Text mining : Classification, clustering, and applications, chapter Topic Models, Chapman & Hall/CRC, 2009.
2 Blei, D.M., Ng, A.Y., and Jordan, M.I., Latent dirichlet allocation, Journal of Machine Learning Research, 3(Jan), 2003, pp. 993-1022.
3 Chowdhury, G.G., Natural language processing, Annual Review of Information Science and Technology, 2003, Vol. 37, No. 1, pp. 51-89.   DOI
4 Curran, C.-S. and Leker, J., Patent indicators for monitoring convergence-examples from NFF and ICT, Technological Forecasting and Social Change, 2011, Vol. 78, No. 2, pp. 256-273.   DOI
5 Galbraith, B. and McAdam, R., The convergence of ICT, policy, intermediaries and society for technology transfer : evidence from European innovation projects, Taylor & Francis, 2013.
6 Geum, Y., Kim, C., Lee, S., and Kim, M.S., Technological convergence of IT and BT : evidence from patent analysis, Etri Journal, 2012, Vol. 34, No. 3, pp. 439-449.   DOI
7 Hanneman, R.A. and Riddle, M., Introduction to social network methods, University of California Riverside, 2005.
8 Ingersoll, G.S., Morton, T.S., and Farris, A.L., Taming text : how to find, organize, and manipulate it : Manning Publications Co., 2013.
9 Jeong, B. and Yoon, J., Competitive intelligence analysis of augmented reality technology using patent information, Sustainability, 2017, Vol. 9, No. 4, p. 497.   DOI
10 Jeong, B., Yoon, J., and Lee, J.-M., Social media mining for product planning : A product opportunity mining approach based on topic modeling and sentiment analysis, International Journal of Information Management, 2018.
11 Jo, J.-H., Chung, Y.-T., Choi, S.-W., and Ok, C., Unstructured Data Quantification Scheme Based on Text Mining for User Feedback Extraction, Journal of Society of Korea Industrial and Systems Engineering, 2018, Vol. 41, No. 4, pp. 131-137.   DOI
12 Karvonen, M. and Kassi, T., Patent citations as a tool for analysing the early stages of convergence, Technological Forecasting and Social Change, 2013, Vol. 80, No. 6, pp. 1094-1107.   DOI
13 Kim, E., Cho, Y., and Kim, W., Dynamic patterns of technological convergence in printed electronics technologies : patent citation network, Scientometrics, 2014, Vol. 98, No. 2, pp. 975-998.   DOI
14 Kim, J., Jeong, B., and Yoon, J., A Technology Planning Approach Based on Network and Growth Curve Analyses : the Case of Augmented Reality Patents, Journal of the Korean Institute of Industrial Engineers, 2016, Vol. 42, No. 5, pp. 337-351.   DOI
15 Kim, T., Choi, H., and Lee, H., A Study on the Research Trends in Fintech using Topic Modeling, Journal of the Korea Academia-Industrial cooperation Society, 2016, Vol. 17, No. 11, pp. 670-681.   DOI
16 Ko, N., Jeong, B., Choi, S., and Yoon, J., Identifying Product Opportunities Using Social Media Mining : Application of Topic Modeling and Chance Discovery Theory, IEEE Access, 2018, Vol. 6, pp. 1680-1693.   DOI
17 Lee, D., Choi, H., Jeong, B., and Yoon, J., Monitoring Bio-fuel Technology Using Patent Text Mining, The Journal of Intellectual Property, 2018, Vol. 13, No. 1, pp. 285-312.   DOI
18 Lu, Y., Mei, Q., and Zhai, C., Investigating task performance of probabilistic topic models : an empirical study of PLSA and LDA, Information Retrieval, 2011, Vol. 14, No. 2, pp. 178-203.   DOI
19 Lee, J., Jeong, B., Ko, N., Oh, S., and Yoon, J., A Problem-Solution based Patent Text Mining Approach for Technological Competition Intelligence Analysis, The Journal of Intellectual Property, 2018, Vol. 13, No. 3, pp. 171-204.   DOI
20 Lee, P.-C., Su, H.-N., and Chan, T.-Y., Assessment of ontology-based knowledge network formation by Vector- Space Model, Scientometrics, 2010, Vol. 85, No. 3, pp. 689-703.   DOI
21 Miyazaki, K. and Islam, N., Nanotechnology systems of innovation-An analysis of industry and academia research activities, Technovation, 2007, Vol. 27, No. 11, pp. 661-675.   DOI
22 No, H.J. and Park, Y., Trajectory patterns of technology fusion : Trend analysis and taxonomical grouping in nanobiotechnology, Technological Forecasting and Social Change, 2010, Vol. 77, No. 1, pp. 63-75.   DOI
23 Oh, S., Choi, H., and Yoon, J., Monitoring Augmented Reality Technology Using Topic Modeling of Patents, Journal of the Korean Institute of Industrial Engineers, 2017, Vol. 43, No. 3, pp. 213-228.   DOI
24 Park, E.L. and Cho, S., KoNLPy : Korean natural language processing in Python, In Proceedings of the 26th Annual Conference on Human & Cognitive Language Technology, 2014, pp. 133-136.
25 Patel, U., Hatay, E., D'Arcy, M., Zand, G., and Fazli, P., Setting Up the Beam for Human-Centered Service Tasks, 2017, arXiv preprint arXiv : 1710.06831.
26 Rafols, I. and Meyer, M., How cross-disciplinary is bionanotechnology? Explorations in the specialty of molecular motors, Scientometrics, 2007, Vol. 70, No. 3, pp. 633-650.   DOI
27 Takeda, Y., Mae, S., Kajikawa, Y., and Matsushima, K., Nanobiotechnology as an emerging research domain from nanotechnology : A bibliometric approach, Scientometrics, 2009, Vol. 80, No. 1, pp. 23-38.   DOI
28 Redman, C.L., Grove, J.M., and Kuby, L.H., Integrating social science into the long-term ecological research (LTER) network : social dimensions of ecological change and ecological dimensions of social change, Ecosystems, 2004, Vol. 7, No. 2, pp. 161-171.   DOI
29 Schmidhuber, J., Deep learning in neural networks : An overview, Neural Networks, 2015, Vol. 61, pp. 85-117.   DOI
30 Scott, J., Social network analysis : Sage, 2017.
31 Wang, B., Liu, S., Ding, K., Liu, Z., and Xu, J., Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis : a case study in LTE technology, Scientometrics, 2014, Vol. 101, No. 1, pp. 685-704.   DOI
32 Wilson, E.O., Consilience : the unity of science, New York : Alfred A. Knopf., 1998.
33 Yoon, B. and Park, Y., A text-mining-based patent network : Analytical tool for high-technology trend, The Journal of High Technology Management Research, 2004, Vol. 15, No. 1, pp. 37-50.   DOI
34 Berman, F.D. and Brady, H.E., NSF SBE-CISE workshop on cyberinfrastructure and the social sciences : National Science Foundation Arlington, 2005.