Skip to main content

Transdisciplinarity and Digital Humanities: Lessons Learned from Developing Text-Mining Tools for Textual Analysis

  • Chapter
Understanding Digital Humanities

Abstract

In recent years, with the emergence of Information and Communication Technologies (ICTs) and other social and political factors, national and international research funding councils have increasingly emphasised that research in the humanities should engage with data-intensive and evidence based academic activities, as those in natural sciences and engineering do. As stated in the description of the cross-nation and cross-discipline ‘Digging into Data Challenge’ programme,1 a call for ‘data-driven inquiry’ or ‘cyber scholarship’ has emerged as a result of hoping to inspire innovative research methods, to transform the nature of social scientific enquiry, and to create new opportunities for interdisciplinary collaboration on problems of common interest.2

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

  • Bammer, G. (2008), ‘Enhancing Research Collaboration: Three Key Management Challenges’, Research Policy 37(5): 875–887.

    Article  Google Scholar 

  • Barry, A., Born, G. and Weszkalnys, G. (2008), ‘HYPERLINK “http://dx.doi.org/10.1080/03085140701760841” Logics of Interdisciplinarity’, Economy and Society 37(1): 20–49.

    Article  Google Scholar 

  • Barthes, R. (1977), Image Music Text (London: Harper Collins).

    Google Scholar 

  • Beaulieu, A., Scharnhorst, A., and Wouters, P. (2007), ‘Not Another Case Study: A Middle-Range Interrogation of Ethnographic Case Studies in the Exploration of e-Science’, Science, Technology, & Human Values 32(6): 672–92.

    Article  Google Scholar 

  • Bolden, R., and Moscarola, J. (2000), ‘Bridging the Quantitative-Qualitative Divide: The Lexical Approach to Textual Data Analysis’, Social Science Computer Review 18(4): 450–60.

    Article  Google Scholar 

  • Brachman, R. and Anand, T. (1996), ‘The Process of Knowledge Discovery in Databases: A Human-Centered Approach’, in U. Fayyad et. al. (eds), Advances in Knowledge, Discovery,and Data Mining (Menlo Park, CA: AAAI Press, 37–58).

    Google Scholar 

  • Christian, B. (2011), ‘Mind vs. Machine’. The Atlantic. URL: http://www.theatlantic.com/magazine/archive/2011/03/mind-vs-machine/8386/. Retrieved on 23 Apr 2011.

    Google Scholar 

  • Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. (1996), ‘From Data Mining to Knowledge Discovery in Databases’, AI Magazine 17(3): 37–54.

    Google Scholar 

  • Fiore, S. M. (2008), ‘Interdisciplinarity as Teamwork: How the Science of Teams Can Inform Team Science’, Small Group Research 39(3): 251–77.

    Article  Google Scholar 

  • Flinterman, J. F., Teclemariam-Mesbah, R., Broerse, J. E. W., Bunders, J. F. G. (2001),‘Transdisciplinarity: The New Challenge for Biomedical Research’, Bulletin of Science Technology Society 21(4): 253–266.

    Article  Google Scholar 

  • Fry, J. (2003), The cultural shaping of scholarly communication within academic specialisms (Unpublished Ph.D. Thesis, University of Brighton).

    Google Scholar 

  • Fry, J. (2004), ‘The Cultural Shaping of ICTs within Academic Fields: Corpus-based Linguistics as a Case Study’, Literary and Linguistic Computing 19(3): 303–319.

    Article  Google Scholar 

  • Fry, J. (2006), ‘Scholarly Research and Information Practices: A Domain Analytic Approach’, Information Processing and Management 42(1): 299–316.

    Article  Google Scholar 

  • Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., Trow, M. (1994), The New Production of Knowledge: the Dynamics of Science and Research in Contemporary Societies (London: Sage).

    Google Scholar 

  • Hessels, L. K. and van Lente, H. (2008), ‘Re-thinking New Knowledge Production: A Literature Review and a Research Agenda’, Research Policy 37: 740–760.

    Article  Google Scholar 

  • Huutoniemi, K., Klein, J. T., Bruun, H., & Hukkinen, J. (2010), ‘Analyzing Interdisciplinarity: Typology and Indicators’, Research Policy 39(1): 79–88.

    Article  Google Scholar 

  • Jankowski, N. (ed.) (2009), E-Research – Transformation in Scholarly Practice (New York: Routledge).

    Google Scholar 

  • Klein, J. T. (1990), Interdisciplinarity: History, Theory and Practice (Detroit: Wayne State University).

    Google Scholar 

  • Kling, R., and McKim, G. (2000), ‘Not Just a Matter of Time: Field Differences and the Shaping of Electronic Media in Supporting Scientific Communication’, Journal of the American Society for Information Science 51(14): 1306–20.

    Article  Google Scholar 

  • Knorr-Cetina, K. (1982), ‘Scientific Communities of Transepistemic Arenas of Research? A Critique of Quasi-Economic Models of Science’, Social Studies of Science 12: 101–30.

    Article  Google Scholar 

  • Koenig, T. (2004), ‘Reframing Frame Analysis: Systematizing the Empirical Identification of Frames Using Qualitative Data Analysis Software’, Paper Presented at the Annual Meeting of the American Sociological Association, Hilton San Francisco & Renaissance

    Google Scholar 

  • Parc 55 Hotel, San Francisco, CA, August 14, 2004.

    Google Scholar 

  • Koenig, T. (2006), ‘Compounding Mixed-Methods Problems in Frame Analysis through Comparative Research’, Qualitative Research 6(1): 61–76.

    Article  Google Scholar 

  • Kurgan, L. and Musilek, P. (2006), ‘A Survey of Knowledge Discovery and Data Mining Process Models’, The Knowledge Engineering Review 21(1): 1–24.

    Article  Google Scholar 

  • Latour, B. (1987), Science in Action: How to Follow Scientists and Engineers Through Society (Cambridge, MA: Harvard University Press).

    Google Scholar 

  • Latour, B. and Woolgar, S. (1979), Laboratory Life: The Social Construction of Scientific Facts (London: Sage Publications Ltd.).

    Google Scholar 

  • Mattila, E. (2005), ‘Interdisciplinarity ‘in the making’: Modelling infectious diseases’,Perspectives on Science 13 (4): 531–553.

    Article  Google Scholar 

  • Morillo, F., Bordons, M., and Gómez, I. (2003), ‘Interdisciplinarity in Science: A Tentative Typology of Disciplines and Research Areas’, Journal of the American Society for Information Science and Technology 54: 1237–49.

    Article  Google Scholar 

  • Nasukawa, T., and Nagano, T. (2001). ‘Text Analysis and Knowledge Mining System’, IBM Systems Journal 40(4): 967–84.

    Article  Google Scholar 

  • Pieri, E. (2009), ‘Sociology of Expectation and the e-Social Science Agenda’, Information Communication and Society 12(7): 1103–18.

    Article  Google Scholar 

  • Rosenfield, P. L. (1992), ‘The Potential of Transdisciplinary Research for Sustaining and Extending Linkages between the Health and Social Sciences’, Social Science Med. 35(11): 1343–1357.

    Article  Google Scholar 

  • Rossini, F. A., and Porter, A. L. (1979), ‘Frameworks for Integrating Interdisciplinary Research’, Research Policy 8: 70–9.

    Article  Google Scholar 

  • Schroeder, R. & Fry, J. (2007), ‘Social Science Approaches to e-Science: Framing an Agenda’, JCMC 12(2) http://jcmc.indiana.edu/vol12/issue2/schroeder.html.

    Google Scholar 

  • Schummer, J. (2004), ‘Multidisciplinarity, Interdisciplinarity, and Patterns of Research Collaboration in Nanoscience and Nanotechnology’, Scientometrics 59(3): 425–465.

    Article  Google Scholar 

  • Seale, C., Charteris-Black, J., and Ziebland, S. (2006a), ‘Gender, Cancer Experience and Internet Use: A Comparative Keyword Analysis of Interviews and Online Cancer Support Groups, Social Science and Medicine 62(10): 2577–90.

    Article  Google Scholar 

  • Seale, C., Anderson, E., and Kinnersley, P. (2006b), ‘Treatment Advice in Primary Care: A Comparative Study of Nurse Practitioners and General Practitioners’, Journal of Advanced Nursing 54(5): 1–8.

    Article  Google Scholar 

  • Toulmin, S. (1972), Human Understanding: Vol. 1. The Collective Use and Development of Concepts (Princeton, NJ: Princeton University Press).

    Google Scholar 

  • Uramoto, N., et al. (2004). ‘A Text-Mining System for Knowledge Discovery from Biomedical Documents, IBM Systems Journal 43(3): 516–33.

    Article  Google Scholar 

  • Weingart, P and Stehr, N. (eds) (2000), Practicing Interdisciplinarity (Toronto: University of Toronto Press).

    Google Scholar 

  • Whitley, R. (1984), The intellectual and social organization of the sciences (Oxford: Clarendon Press).

    Google Scholar 

  • Zheng, Y., Venters, W., and Cornford, T. (2011), ‘Collective Agility, Paradox and Organizational Improvisation: The Development of a Particle Physics Grid’, Information Systems Journal 21(3): doi: 10.1111/j.1365–2575.2010.00360.x.

    Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Copyright information

© 2012 Yu-wei Lin

About this chapter

Cite this chapter

Lin, Yw. (2012). Transdisciplinarity and Digital Humanities: Lessons Learned from Developing Text-Mining Tools for Textual Analysis. In: Berry, D.M. (eds) Understanding Digital Humanities. Palgrave Macmillan, London. https://doi.org/10.1057/9780230371934_16

Download citation

Publish with us

Policies and ethics