1. Scientific Web Intelligence The Birth of a New Research Field Mike Thelwall Statistical Cybermetrics Research Group University of Wolverhampton, UK

2. The Problem To map patterns of communication between researchers in a country based upon university web sites Patterns of communication are also mapped based upon journal citations or journal title words Provides useful information about the structure and evolution of research fields Can identify previously unknown field connections Web analysis could illustrate wider and more current patterns

3. Part 1: Hyperlink Analysis Citation counts are known to be reasonable indicators of research quality but is the same true for inlink counts? Counts of links to universities within a country can correlate significantly with measures of research productivity The significance of this result is in giving ‘permission’ to investigate the use of inter-university links for researching scholarly communication

4. Links to UK universities against their research productivity The reason for the strong correlation is the quantity of Web publication, not its quality This is different to citation analysis

5. Most links are only loosely related to research 90% of links between UK university sites have some connection with scholarly activity, including teaching and research But less than 1% are equivalent to citations So link counts do not measure research dissemination but are more a natural by-product of scholarly activity Cannot use link counts to assess research Can use link counts to track an aspect of communication

6. Some Hyperlink Patterns Patterns in counts of links between university Web sites

7. Universities tend to link to neighbours

8. Universities cluster geographically

9. Language is a factor in international interlinking English the dominant language for Web sites in the Western EU In a typical country, 50% of pages are in the national language(s) and 50% in English Non-English speaking extensively interlink in English {Research with Rong Tang & Liz Price}

10. Can map patterns of international communication Counts of links between EU universities in Swedish are represented by arrow thickness.

11. Counts of links between EU universities in French are represented by arrow thickness.

12. Which language???

14. Disciplinary Patterns Links and subject areas

15. Linking patterns vary enormously by discipline No evidence of a significant geographic trend Disciplinary differences in the extent of interlinking: e.g., history Web use is very low, Chemistry is very high Individual research projects can have an enormous impact upon individual departments E.g. Arts web sites are often for specific exhibitions or for digital media projects Links not frequent enough to reliably reveal patterns of interdiscipliniarity

16. Stretching links: colinks, couplings For the UK academic Web, about 42% of domains connected by links alone host similar disciplines, and about 43% connected by links, colinks and couplings But over 100 times more domains are colinked or coupled than are directly linked Links in any form are less than 50% reliable as indicators of subject similarity

17. Text Mining Approaches Hyperlinks are not frequent enough or systematic enough to yield reliable evidence of connections at a low level Alternative is to look for words in common E.g., the frequency with which words associated with psychology are found in computer science web sites Clustering web pages/sites based upon word occurrences (c.f. journal title word clustering)

18. Text clustering – early results WordFrequencyDomainsImportance business598064080.005902 marketing169872420.004476 finance83002170.002826 economics155092610.002726 banking20101230.002717 management767544650.002569 sitemap2419620.001874 accounting81621970.001613 auckland556044140.001546

19. Which discipline? WordFrequencyDomainsImportance template33561470.001355 assignment156102400.001186 copyright167802780.001166 changed71722840.001152 sst199330.001071 semester183643190.001009 systems445214510.000949 lab77092610.000861 comments169313540.000842

20. Scientific Web Intelligence Standard hyperlink and text mining approaches are inadequate for identifying low level inter-subject connections Either extensive human intervention or artificial intelligence techniques needed to extract useful information Hence the founding of Scientific Web Intelligence

21. Scientific Web Intelligence Objective: to combine techniques from Information Science, Web Mining and Web Intelligence to extract patterns of interdiscipliniarity from university Web sites

22. Opportunities Develop graphical techniques to display the data Develop AI/Data Mining techniques to analyse the data Extend the techniques to other domains – e.g. business web intelligence