The document discusses the origins and early research in the field of webometrics. It describes how webometrics emerged from the availability of web link data and how early studies analyzed link structures between web pages and sites. The document also summarizes two key early webometric studies: one that analyzed small-world link networks across UK university websites using graph theory, and another that examined the role of different web page genres in connecting and spreading information between university sites.

1. Webometrics 1.0 from AltaVista to Small Worlds and Genre Drift Lennart Björneborn Royal School of Library and Information Science [email_address] NORSLIS PhD course in informetrics Umeå 18.6.2008

3. WWW = largest network with available connectivity data Wood et al. (1995)

4. WWW = collaborative weaving = macro-level aggregations of micro-level interactions = reflect social, cultural formations Wood et al. (1995)

5. = keep track of ”the complex web of relationships between people, programs, machines and ideas” (Tim Berners-Lee, 1997) Wood et al. (1995) WWW

7. birth of webometrics: access to link data* linkdomain:norslis.net -site:norslis.net link:www.norslis.net -site:norslis.net (* cf. breakthrough of bibliometrics: access to citation data)

8. linkdomain:norslis.net -site:norslis.net

16. http:// www.scit.wlv.ac.uk /~cm1993/ mtpublications.html

17. small-world link analysis Björneborn (2004). Small-world link structures across an academic Web space: A library and information science approach . PhD Thesis. www.db.dk/LB based on graph theory and social network analysis

18. graph theory - Leonhard Euler (1707-1783), Königsberg (Wilson & Watkins 1990)

26. ‘ corona’ graph model reachability structures 1893 SCC Strongest Connected Component 96 IN-Tendrils connected from IN 2660 OUT reachable from SCC 626 IN traversable to SCC 55 OUT-Tendrils connected to OUT 7 Tube connecting IN to OUT 2332 Dis-connected ( Björneborn 2004)

27. 10 seed nodes (stratified sampling in SCC component) 10 path nets with all shortest link paths between five pairs of topically dissimilar subsites Ophthalmology Dept, [eye research] Oxford Palaeontology Research Group, Earth Sciences Dept, Bristol Mathematics Dept, Glasgow Caledonian Chemistry Dept, Glasgow Atmospheric, Oceanic and Planetary Physics , Oxford eye.ox.ac.uk Geography Dept, Plymouth geog.plym.ac.uk palaeo.gly.bris.ac.uk Speech Research Group, Linguistics Dept, Essex speech.essex.ac.uk maths.gcal.ac.uk Psychology Dept, Manchester psy.man.ac.uk chem.gla.ac.uk Economics Dept, Southampton economics.soton. ac.uk atm.ox.ac.uk Faculty of Humanities and Social Sciences , Portsmouth hum.port.ac.uk

28. .ac.uk .uk cfd.me.umist.ac.uk ercoftac.mech.surrey.ac.uk cajun.cs.nott.ac.uk ukoln.bath.ac.uk cs.man.ac.uk ashmol.ox.ac.uk collections.ucl.ac.uk vlmp.museophile.sbu.ac.uk shortest link path

29. path net = ‘mini’ small world transversal link path net = all shortest link paths between two given nodes (subsites) network analysis tool = Pajek  adjacency matrix ( Björneborn 2006)

34. meta genres

35. genre pairs

36. web of genres genre network graph extracted with Pajek software © Björneborn

39. questions?

40. read more: Björneborn (2004). Small-world link structures across an academic web space : A library and information science approach. PhD dissertation. www.db.dk/LB Björneborn (2006). ‘Mini small worlds’ of shortest link paths crossing domain boundaries in an academic Web space. Scientometrics , 68(3): 395-414. Björneborn (forthcoming). Genre connectivity and genre drift in a web of genres. In: Mehler et al. Genres on the Web: Corpus Studies and Computational Models .