Enriching Literature Reviews with Text Mining Tools Case: Group Support Systems

1. Enriching Literature Reviews with Text Mining ToolsCase: Group Support Systems Ph.D. Johanna Bragge / HSE / Business Technology / ISS http://www.hse.fi/EN/HKI/B/Johanna_Bragge The presentation is based on Bragge J., Relander S., Sunikka A. and Mannonen P. (2007) “Enriching Literature Reviews with Computer-Assisted Research Mining. Case: Profiling Group Support Systems Research”, Proceedings of 40th HICSS Conference, Hawaii, USA.

2. Structure of presentation • Objectives of our HICSS´07 paper • What is ”research profiling”? • Profiling research on Group Support Systems • Dimensions of research profiling • From undergrad class papers and ”one-nighters” to dissertation or other major research projects • Possibilities of ISI WoS Analysis tool • Conclusions

3. Objectives of our HICSS´07 paper • Extend the notion of a traditional literature review • into the domain of research profiling • Present a practical case study • Group (Decision) Support Systems research • Briefly overview the capabilities of VantagePoint • Text-mining software originally developed at the Georgia Institute of Technology, USA (currently SearchTech Inc.)

4. ”Can we improve on the traditional ’literature review’?” • Science and technology abstracts are literally at our fingertips in R&D databases • Search engines enable rapid and effective collection of records relating to one’s research interests • Analytical software helps elicit useful information from the searches (even if thousands of abstracts) to gain perspective on ones’ research context. • ”This enhanced literature review – ’research profiling’– should become standard research practice.” Source: Porter, Kongthon and Lu (2002), ”From Traditional Literature Reviews to ’Research Profiling’”, Scientometrics, Vol. 53, No. 3, 351-370. AVAILABLE in SpringerLinkdatabase.

5. Augmenting, not replacing! • Research profiling aims to augment, not replace, the traditional literature review • helping to fulfill purposes of understanding the structure of the subject, important variables, pertinent methods, and key needs • These aims can be better served by analyzing the whole, rather than just a few parts of the research milieu. • students often limit their perspective to specialized slices of the literature • research streams often lose connection to other research activities Porter et al. (2002, p. 351).

6. Comparison of traditional literature reviews and research profiling Porter et al. (2002, p. 353).

7. The research profiling process based on Herbert Simon’s Decision Phases Source: Adapted from Porter and Cunningham (2005).

8. Selection of databases Fundamental research • Science Citation Index, ISI • MEDLINE • Chem abstracts • INSPEC (by IEE) • EI Compendex • Derwent World Patent Index • ABI Inform (ProQuest) • Lexis Nexis Commercial application Source: Porter & Cunningham (2005, p. 83)

9. Case: Profiling Group Support Systems Research • Research question: Past, present and future of GSS • Level of maturity / saturation? • Who? What? When? • What’s hot? Are there any emerging themes? • Etc. • Search words used: • group support system(s), group decision support system(s), electronic meeting system(s) • Database used: INSPEC by IEE • Covers more than 3.850 journals and 2.200 conference proceedings • Final sample: 2.000 publications from 1982-2005 • The sample was collected in April 2006

10. G(D)SS Publications yearly in INSPEC

11. Top-12 Institutions of GSS research

12. Top-12 Outlets of GSS research

13. Top-7 authors and selected details

14. Key figures of GSS research in 2000-2005 (from 688 out of 2000 publications)

15. Trends in authors’ keywords (non-technology)

16. 5-year trends of various terms

17. Illustration of VantagePoint’s ”DSS-capabilities”

18. Dimensions of research profiling Source: Porter et al. (2002, p. 366)

19. ISI Web of Science’s Analysis tool – suitable for ”one-nighters”

21. Problems occur as the authors may be inserted differently in the database! With VantagePoint these can be cleaned for the purposes of advanced analyses – with simple frequencies ISI works well.

22. More options can be found from the ”Analyze Results: Analyze” button (in the right-hand column of the main search results page). Also possibility to save records to file for graphs.

23. Conclusions • Increasing availability and amount of information • Modern search engines developed • Research profiling uses sophisticated text mining tools for structured science information resources • i.e. abstracts from ISI WoS, Ebsco, ProQuest, INSPEC etc. • Emphasis on content - uncovering research gaps and new scientific domains • Emphasis not on co-citation analysis (SNA tools better for that) • Does not replace traditional literature reviews! • Database limitations, e.g. publication delays and non-standardized contents of different databases • Questions or comments?

24. More references on the foundations and applications of research profiling • Porter, A. L., Kongthon, A. and J.-C. Lu, (2002) "Research Profiling: Improving the Literature Review", Scientometrics, vol. 53, no. 3, pp. 351-370. • Porter, A. L. and S.W. Cunningham (2005), Tech Mining. Exploiting New Technologies for Competitive Advantage, Wiley Series in System Engineering and Management, New Jersey: John Wiley & Sons, Inc. • Bragge, J., and Storgårds, J, (2007) “Profiling Academic Research on Digital Games Using Text Mining Tools”, Proceedings of the Digital Games Research Association’s DIGRA Conference, Tokyo, Japan. • Bragge, J., and Storgårds, J, (2007) “Utilizing Text-Mining Tools to Enrich Traditional Literature Reviews. Case: Digital Games”, Proceedings of the 30th Information Systems Research Seminar in Scandinavia IRIS, Tampere, Finland. • Sunikka, A. and Bragge, J. (2008) “What, Who and Where: Insight into Personalization”, Forthcoming in the Proceedings of the HICSS´-41, Hawaii, USA, January, 2008