, Volume 105, Issue 1, pp 323–335 | Cite as

‘Technology Mining’ bibliometrics analysis: applying network analysis and cluster analysis

  • Farshad MadaniEmail author


According to advances in text mining methods and tools, technology mining, or its brevity ‘tech mining’, is one of recent research areas progressively emerged in technology management area. Over past two decades, this area has been attractive for many scholars in business management, technology management, and computer science departments. The majority of tech mining applications is concentrated on analyzing patents which is also called patent mining by some scholars; moreover, there are some researchers reported tech mining applied to other types of technological documents like R&D reports (Porter and Newman 2011).

Porter as one of pioneers in technology mining has defined ‘tech mining’ in his book (Porter and Cunningham 2005): the application of text mining toolsto science and technology information, informed by understanding of technological innovation processes.Therefore, tech mining has two significant characteristics: (1) using ‘text mining tools’, (2) applied for...


Network Analysis Text Mining Citation Analysis Patent Citation Eigenvector Centrality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

11192_2015_1685_MOESM1_ESM.docx (35 kb)
Supplementary material 1 (DOCX 34 kb)


  1. Alencar, M. S. M., Porter, A. L., & Antunes, A. M. S. (2007). Nanopatenting patterns in relation to product life cycle. Technological Forecasting and Social Change, 40, 1661–1680.Google Scholar
  2. Chen, C. (2004). Information visualization. Berlin: Springer.Google Scholar
  3. Chen, C. (2006). CiteSpace II : Detecting and visualizing emerging trends. Journal of American Society for Information Science and Technology, 57(3), 359–377.CrossRefGoogle Scholar
  4. Chen, C. (2014). “CiteSpac,” [Online].
  5. Chen, C., Zhang, J., & Vogeley, M. S. (2009). Visual analysis of scientific discoveries and knowledge diffusion. In The 12th international conference on scientometrics and informetrics, pp. 14–17.Google Scholar
  6. Chiavetta, D., & Porter, A. (2013). Tech mining for innovation management. Technology Analysis & Strategic Management, 25(6), 617–618.CrossRefGoogle Scholar
  7. Choi, S., Kim, H., Yoon, J., Kim, K., & Lee, J. (2013). An SAO-based text-mining approach for technology roadmapping using patent information. R&D Management, 43(1), 52–74.CrossRefGoogle Scholar
  8. Choi, S., Park, H., Kang, D., Lee, J. Y., & Kim, K. (2012). An SAO-based text mining approach to building a technology tree for technology planning. Expert Systems with Applications, 39(13), 11443–11455.CrossRefGoogle Scholar
  9. Choi, S., Yoon, J., Kim, K., & Kim, C.-H. (2011). SAO network analysis of patents for technology trends identification: A case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells. Scientometrics, 88(3), 863–883.Google Scholar
  10. Dhami M. K., & Olsson, H. (2008). Evolution of the interpersonal conflict paradigm. Judgment and Decision Making, 3(7), 547–569.Google Scholar
  11. Gerken, J. M. (2012). A new instrument for technology monitoring: Novelty in patents measured by semantic patent analysis. Scientometrics, 91(3), 645.CrossRefGoogle Scholar
  12. Geum, Y., Lee, S., Yoon, B., & Park, Y. (2013). Identifying and evaluating strategic partners for collaborative R&D: Index-based approach using patents and publications. Technovation, 33(6–7), 211–224.CrossRefGoogle Scholar
  13. Guo, Y., Huang, L., & Porter, A. L. (2010). The research profiling method applied to nano-enhanced, thin-film solar cells. R&D Management, 40(2), 195–208.Google Scholar
  14. Guo, Y., Ma, T., Porter, A. L., & Huang, L. (2012). Text mining of information resources to inform forecasting innovation pathways. Technology Analysis & Strategic Management, 24(8), 843–861.CrossRefGoogle Scholar
  15. Jeon, J., Lee, C., & Park, Y. (2011). How to use patent information to search potential technology partners in open innovation. Journal of Intellectual Property Rights, 16(5), 385–393.Google Scholar
  16. Kuan, C., Huang, M., & Chen, D. (2013). Capturing and tracking performance of patent portfolio using h-complement area centroid. IEEE Transactions of Engineering Management, 60(3), 496–505.CrossRefGoogle Scholar
  17. Lee, C., Cho, Y., Seol, H., & Park, Y. (2012). A stochastic patent citation analysis approach to assessing future technological impacts. Technological Forecasting and Social Change, 79(1), 16–29.CrossRefGoogle Scholar
  18. Lee, C., Jeon, J., & Park, Y. (2011). Monitoring trends of technological changes based on the dynamic patent lattice: A modified formal concept analysis approach. Technological Forecasting and Social Change, 78(4), 690–702.MathSciNetCrossRefGoogle Scholar
  19. Lee, P.-C., Su, H.-N., & Wu, F.-S. (2010). Quantitative mapping of patented technology—The case of electrical conducting polymer nanocomposite. Technological Forecasting and Social Change, 77(3), 466–478.CrossRefGoogle Scholar
  20. McCulloh, I., Armstrong, H., & Johnson, A. (2013). Social network analysis with applications (p. 46). New Jersey: Wiley.Google Scholar
  21. Park, H., Yoon, J., & Kim, K. (2012). Identifying patent infringement using SAO based semantic technological similarities. Scientometrics, 90(2), 515–529.CrossRefGoogle Scholar
  22. Porter, A. L. (2005). QTIP: Quick technology intelligence processes. Technological Forecasting and Social Change, 72(9), 1070–1081.CrossRefGoogle Scholar
  23. Porter, A. L., & Cunningham, S. W. (2005). Tech mining: Exploiting new technologies for competitive advantage. New Jersey: Wiley.Google Scholar
  24. Porter, A. L., Guo, Y., & Chiavatta, D. (2011). Tech mining: Text mining and visualization tools, as applied to nanoenhanced solar cells. WILEY Interdisciplilnary Reviews: Data Mining and Knowledge Discovery, 1(2), 172–181.Google Scholar
  25. Porter, A., & Newman, N. (2011, January). Mining external R&D. Technovation, no.Google Scholar
  26. Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65.CrossRefzbMATHGoogle Scholar
  27. Tijssen, R. J. (2001). Global and domestic utilization of industrial relevant science: Patent citation analysis of science–technology interactions and knowledge flows. Research Policy, 30(1), 35–54.CrossRefGoogle Scholar
  28. Tonta, Y., & Darvish, H. R. (2010). Diffusion of latent semantic analysis as a research tool: A social network analysis approach. Journal of Informetrics, 4(2), 166–174.CrossRefGoogle Scholar
  29. Xu-kun, H. J. Z. C. W. (2008). The information visualization analysis of the study in international S & T policy, pp. 1–9.Google Scholar
  30. Yoon, B. (2008). On the development of a technology intelligence tool for identifying technology opportunity. Expert Systems with Applications, 35(1–2), 124–135.CrossRefGoogle Scholar
  31. Yoon, J., & Kim, K. (2011). Identifying rapidly evolving technological trends for R&D planning using SAO-based semantic patent networks. Scientometrics, 88(1), 213–228.CrossRefGoogle Scholar
  32. Yoon, B., & Park, Y. (2005). A systematic approach for identifying technology opportunities: Keyword-based morphology analysis. Technological Forecasting and Social Change, 72(2), 145–160.CrossRefGoogle Scholar
  33. Yoon, J., Park, H., & Kim, K. (2013). Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis. Scientometrics, 94(1), 313–331.CrossRefGoogle Scholar
  34. Zhu, D., & Porter, A. L. (2002). Automated extraction and visualization of information for technological intelligence and forecasting. Technological Forecasting and Social Change, 69(5), 495–506.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2015

Authors and Affiliations

  1. 1.Portland State UniversityPortlandUSA

Personalised recommendations