SlideShare a Scribd company logo
1 of 40
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
outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],M.C. Escher: House of Stairs, 1951
WWW = largest network    with available connectivity data Wood et al. (1995)
WWW = collaborative weaving =  macro-level aggregations   of  micro-level interactions = reflect social, cultural formations   Wood et al. (1995)
= keep track of    ”the complex web of relationships    between people, programs,    machines and ideas”   (Tim Berners-Lee, 1997)   Wood et al. (1995) WWW
birth of webometrics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
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)
linkdomain:norslis.net  -site:norslis.net
basic link terminology ,[object Object],[object Object],[object Object],[object Object],[object Object],A B D E G F H C co-links (Björneborn 2004)
some proposed web metrics ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
some related web science ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
webometrics ,[object Object],( Björneborn 2004) informetrics bibliometrics scientometrics webometrics cybermetrics
webometrics ,[object Object],[object Object],[object Object],[object Object],[object Object],informetrics bibliometrics scientometrics webometrics cybermetrics ( Björneborn 2004)
web data collection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
examples of webometric analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
http:// www.scit.wlv.ac.uk /~cm1993/ mtpublications.html
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
graph theory - Leonhard Euler (1707-1783), Königsberg (Wilson & Watkins  1990)
graph theory ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Gross & Yellen (1999).  Graph theory and its applications . E A B C D
graph theory applications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
social network analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
small-world  networks ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],( Watts & Strogatz 1998)
[object Object],[object Object]
[object Object],[object Object],[object Object],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
UK link data   2001 ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
‘ 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)
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
.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
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)
some indicative findings ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
small-world web implications ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
webometric study:   genre connectivity  ,[object Object],[object Object]
[object Object],[object Object],genre connectivity analysis  ,[object Object],[object Object]
meta genres
genre pairs
web of genres genre network graph  extracted with  Pajek  software  ©  Björneborn
genre  connectivity ,[object Object],[object Object],[object Object],[object Object],[object Object]
genre drift + topic drift ,[object Object],[object Object],[object Object]
questions?
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 .

More Related Content

What's hot

Social Networks and Computer Science
Social Networks and Computer ScienceSocial Networks and Computer Science
Social Networks and Computer Sciencedragonmeteor
 
2009 December NodeXL Overview
2009 December NodeXL Overview2009 December NodeXL Overview
2009 December NodeXL OverviewMarc Smith
 
Nitle Model 20090521
Nitle Model 20090521Nitle Model 20090521
Nitle Model 20090521Rebecca Davis
 
Visually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of LifeVisually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of LifeHarish Vaidyanathan
 
New Forms of Data and Scientific Research
New Forms of Data and Scientific ResearchNew Forms of Data and Scientific Research
New Forms of Data and Scientific ResearchDavid De Roure
 
Disc2013 keynote speakers
Disc2013 keynote speakersDisc2013 keynote speakers
Disc2013 keynote speakersHan Woo PARK
 
Webometrics Revisited in Big Data Age_DISC2013
Webometrics Revisited in Big Data Age_DISC2013Webometrics Revisited in Big Data Age_DISC2013
Webometrics Revisited in Big Data Age_DISC2013Han Woo PARK
 
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 20072009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007Marc Smith
 
Mdst3703 ontology-overrated-2012-10-16
Mdst3703 ontology-overrated-2012-10-16Mdst3703 ontology-overrated-2012-10-16
Mdst3703 ontology-overrated-2012-10-16Rafael Alvarado
 
2013 NodeXL Social Media Network Analysis
2013 NodeXL Social Media Network Analysis2013 NodeXL Social Media Network Analysis
2013 NodeXL Social Media Network AnalysisMarc Smith
 
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Xiaohan Zeng
 
Network analysis: People and open source communities
Network analysis: People and open source communitiesNetwork analysis: People and open source communities
Network analysis: People and open source communitiesDawn Foster
 
2009 Node XL Overview: Social Network Analysis in Excel 2007
2009 Node XL Overview: Social Network Analysis in Excel 20072009 Node XL Overview: Social Network Analysis in Excel 2007
2009 Node XL Overview: Social Network Analysis in Excel 2007Marc Smith
 
Ica2012 preconference keynote
Ica2012 preconference keynoteIca2012 preconference keynote
Ica2012 preconference keynoteHan Woo PARK
 
2015 pdf-marc smith-node xl-social media sna
2015 pdf-marc smith-node xl-social media sna2015 pdf-marc smith-node xl-social media sna
2015 pdf-marc smith-node xl-social media snaMarc Smith
 
Dissertation Social Network Sites
Dissertation Social Network SitesDissertation Social Network Sites
Dissertation Social Network SitesXenia K-i
 
Franck Rebillard, Professeur Université Paris 3
Franck Rebillard, Professeur Université Paris 3Franck Rebillard, Professeur Université Paris 3
Franck Rebillard, Professeur Université Paris 3SMCFrance
 

What's hot (19)

Social Networks and Computer Science
Social Networks and Computer ScienceSocial Networks and Computer Science
Social Networks and Computer Science
 
2009 December NodeXL Overview
2009 December NodeXL Overview2009 December NodeXL Overview
2009 December NodeXL Overview
 
Nitle Model 20090521
Nitle Model 20090521Nitle Model 20090521
Nitle Model 20090521
 
Visually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of LifeVisually Exploring Social Participation in Encyclopedia of Life
Visually Exploring Social Participation in Encyclopedia of Life
 
New Forms of Data and Scientific Research
New Forms of Data and Scientific ResearchNew Forms of Data and Scientific Research
New Forms of Data and Scientific Research
 
MDST 3703 F10 Seminar 4
MDST 3703 F10 Seminar 4MDST 3703 F10 Seminar 4
MDST 3703 F10 Seminar 4
 
Resume2015 (3)
Resume2015 (3)Resume2015 (3)
Resume2015 (3)
 
Disc2013 keynote speakers
Disc2013 keynote speakersDisc2013 keynote speakers
Disc2013 keynote speakers
 
Webometrics Revisited in Big Data Age_DISC2013
Webometrics Revisited in Big Data Age_DISC2013Webometrics Revisited in Big Data Age_DISC2013
Webometrics Revisited in Big Data Age_DISC2013
 
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 20072009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007
2009 - Node XL v.84+ - Social Media Network Visualization Tools For Excel 2007
 
Mdst3703 ontology-overrated-2012-10-16
Mdst3703 ontology-overrated-2012-10-16Mdst3703 ontology-overrated-2012-10-16
Mdst3703 ontology-overrated-2012-10-16
 
2013 NodeXL Social Media Network Analysis
2013 NodeXL Social Media Network Analysis2013 NodeXL Social Media Network Analysis
2013 NodeXL Social Media Network Analysis
 
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...
Social Network Analysis: What It Is, Why We Should Care, and What We Can Lear...
 
Network analysis: People and open source communities
Network analysis: People and open source communitiesNetwork analysis: People and open source communities
Network analysis: People and open source communities
 
2009 Node XL Overview: Social Network Analysis in Excel 2007
2009 Node XL Overview: Social Network Analysis in Excel 20072009 Node XL Overview: Social Network Analysis in Excel 2007
2009 Node XL Overview: Social Network Analysis in Excel 2007
 
Ica2012 preconference keynote
Ica2012 preconference keynoteIca2012 preconference keynote
Ica2012 preconference keynote
 
2015 pdf-marc smith-node xl-social media sna
2015 pdf-marc smith-node xl-social media sna2015 pdf-marc smith-node xl-social media sna
2015 pdf-marc smith-node xl-social media sna
 
Dissertation Social Network Sites
Dissertation Social Network SitesDissertation Social Network Sites
Dissertation Social Network Sites
 
Franck Rebillard, Professeur Université Paris 3
Franck Rebillard, Professeur Université Paris 3Franck Rebillard, Professeur Université Paris 3
Franck Rebillard, Professeur Université Paris 3
 

Similar to Webometrics 1.0 from AltaVista to Small Worlds and Genre Drift

e-Research: A Social Informatics Perspective
e-Research: A Social Informatics Perspectivee-Research: A Social Informatics Perspective
e-Research: A Social Informatics PerspectiveEric Meyer
 
The End(s) of e-Research
The End(s) of e-ResearchThe End(s) of e-Research
The End(s) of e-ResearchEric Meyer
 
OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederOII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederEric Meyer
 
Scholarship in the Digital Age
Scholarship in the Digital AgeScholarship in the Digital Age
Scholarship in the Digital AgeEric Meyer
 
Mining and Supporting Community Structures in Sensor Network Research
Mining and Supporting Community Structures in Sensor Network ResearchMining and Supporting Community Structures in Sensor Network Research
Mining and Supporting Community Structures in Sensor Network ResearchMarko Rodriguez
 
It’s a “small world” after all
It’s a “small world” after allIt’s a “small world” after all
It’s a “small world” after allquanmengli
 
Interpreting sslar
Interpreting sslarInterpreting sslar
Interpreting sslarRatzman III
 
A Survey Of The First 20 Years Of Research On Semantic Web And Linked Data
A Survey Of The First 20 Years Of Research On Semantic Web And Linked DataA Survey Of The First 20 Years Of Research On Semantic Web And Linked Data
A Survey Of The First 20 Years Of Research On Semantic Web And Linked DataKelly Lipiec
 
Jankowski, Vks E Research Slidecast, 26 June2008
Jankowski, Vks E Research Slidecast, 26 June2008Jankowski, Vks E Research Slidecast, 26 June2008
Jankowski, Vks E Research Slidecast, 26 June2008Nick Jankowski
 
Complex Networks Analysis @ Universita Roma Tre
Complex Networks Analysis @ Universita Roma TreComplex Networks Analysis @ Universita Roma Tre
Complex Networks Analysis @ Universita Roma TreMatteo Moci
 
New Metrics for New Media Bay Area CIO IT Executives Meetup
New Metrics for New Media Bay Area CIO IT Executives MeetupNew Metrics for New Media Bay Area CIO IT Executives Meetup
New Metrics for New Media Bay Area CIO IT Executives MeetupTatyana Kanzaveli
 
Wimmics Research Team Overview 2017
Wimmics Research Team Overview 2017Wimmics Research Team Overview 2017
Wimmics Research Team Overview 2017Fabien Gandon
 
How to utilize ‘big data’ on SNS for academic purpose?
How to utilize ‘big data’ on SNS  for academic purpose?How to utilize ‘big data’ on SNS  for academic purpose?
How to utilize ‘big data’ on SNS for academic purpose?Han Woo PARK
 
A Never-Ending Project for Humanity Called “the Web”
A Never-Ending Project for Humanity Called “the Web”A Never-Ending Project for Humanity Called “the Web”
A Never-Ending Project for Humanity Called “the Web”Fabien Gandon
 
Mapping big data science
Mapping big data scienceMapping big data science
Mapping big data scienceHan Woo PARK
 

Similar to Webometrics 1.0 from AltaVista to Small Worlds and Genre Drift (20)

e-Research: A Social Informatics Perspective
e-Research: A Social Informatics Perspectivee-Research: A Social Informatics Perspective
e-Research: A Social Informatics Perspective
 
The End(s) of e-Research
The End(s) of e-ResearchThe End(s) of e-Research
The End(s) of e-Research
 
OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
OII Summer Doctoral Programme 2010: Global brain by Meyer & SchroederOII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
OII Summer Doctoral Programme 2010: Global brain by Meyer & Schroeder
 
Mike thelwall ritu
Mike thelwall rituMike thelwall ritu
Mike thelwall ritu
 
DREaM Event 2: Louise Cooke
DREaM Event 2: Louise CookeDREaM Event 2: Louise Cooke
DREaM Event 2: Louise Cooke
 
Scholarship in the Digital Age
Scholarship in the Digital AgeScholarship in the Digital Age
Scholarship in the Digital Age
 
Mining and Supporting Community Structures in Sensor Network Research
Mining and Supporting Community Structures in Sensor Network ResearchMining and Supporting Community Structures in Sensor Network Research
Mining and Supporting Community Structures in Sensor Network Research
 
It’s a “small world” after all
It’s a “small world” after allIt’s a “small world” after all
It’s a “small world” after all
 
Interpreting sslar
Interpreting sslarInterpreting sslar
Interpreting sslar
 
A Survey Of The First 20 Years Of Research On Semantic Web And Linked Data
A Survey Of The First 20 Years Of Research On Semantic Web And Linked DataA Survey Of The First 20 Years Of Research On Semantic Web And Linked Data
A Survey Of The First 20 Years Of Research On Semantic Web And Linked Data
 
Jankowski, Vks E Research Slidecast, 26 June2008
Jankowski, Vks E Research Slidecast, 26 June2008Jankowski, Vks E Research Slidecast, 26 June2008
Jankowski, Vks E Research Slidecast, 26 June2008
 
Complex Networks Analysis @ Universita Roma Tre
Complex Networks Analysis @ Universita Roma TreComplex Networks Analysis @ Universita Roma Tre
Complex Networks Analysis @ Universita Roma Tre
 
New Metrics for New Media Bay Area CIO IT Executives Meetup
New Metrics for New Media Bay Area CIO IT Executives MeetupNew Metrics for New Media Bay Area CIO IT Executives Meetup
New Metrics for New Media Bay Area CIO IT Executives Meetup
 
Wimmics Research Team Overview 2017
Wimmics Research Team Overview 2017Wimmics Research Team Overview 2017
Wimmics Research Team Overview 2017
 
intro to sna.ppt
intro to sna.pptintro to sna.ppt
intro to sna.ppt
 
Dh usp 2013
Dh usp 2013Dh usp 2013
Dh usp 2013
 
How to utilize ‘big data’ on SNS for academic purpose?
How to utilize ‘big data’ on SNS  for academic purpose?How to utilize ‘big data’ on SNS  for academic purpose?
How to utilize ‘big data’ on SNS for academic purpose?
 
A Never-Ending Project for Humanity Called “the Web”
A Never-Ending Project for Humanity Called “the Web”A Never-Ending Project for Humanity Called “the Web”
A Never-Ending Project for Humanity Called “the Web”
 
Mapping big data science
Mapping big data scienceMapping big data science
Mapping big data science
 
Usp dh 2013
Usp dh 2013Usp dh 2013
Usp dh 2013
 

More from Lennart Björneborn

Social navigation, user-to-user mediation and participatory mediation spaces
Social navigation, user-to-user mediation and participatory mediation spacesSocial navigation, user-to-user mediation and participatory mediation spaces
Social navigation, user-to-user mediation and participatory mediation spacesLennart Björneborn
 
Micro-serendipity: Meaningful coincidences in everyday life shared on Twitter
Micro-serendipity: Meaningful coincidences in everyday life shared on TwitterMicro-serendipity: Meaningful coincidences in everyday life shared on Twitter
Micro-serendipity: Meaningful coincidences in everyday life shared on TwitterLennart Björneborn
 
Bibliotek 2.0, brugspotentialer og brugerinvolvering
Bibliotek 2.0, brugspotentialer og brugerinvolveringBibliotek 2.0, brugspotentialer og brugerinvolvering
Bibliotek 2.0, brugspotentialer og brugerinvolveringLennart Björneborn
 
Web 2.0, brugerinvolvering og sociale teknologier
Web 2.0, brugerinvolvering og sociale teknologierWeb 2.0, brugerinvolvering og sociale teknologier
Web 2.0, brugerinvolvering og sociale teknologierLennart Björneborn
 
Serendipitet og brugerskabt formidling
Serendipitet og brugerskabt formidlingSerendipitet og brugerskabt formidling
Serendipitet og brugerskabt formidlingLennart Björneborn
 
På sporet efter hinanden - Web 2.0 og social navigation
På sporet efter hinanden - Web 2.0 og social navigationPå sporet efter hinanden - Web 2.0 og social navigation
På sporet efter hinanden - Web 2.0 og social navigationLennart Björneborn
 

More from Lennart Björneborn (7)

ASIST2016-LB
ASIST2016-LBASIST2016-LB
ASIST2016-LB
 
Social navigation, user-to-user mediation and participatory mediation spaces
Social navigation, user-to-user mediation and participatory mediation spacesSocial navigation, user-to-user mediation and participatory mediation spaces
Social navigation, user-to-user mediation and participatory mediation spaces
 
Micro-serendipity: Meaningful coincidences in everyday life shared on Twitter
Micro-serendipity: Meaningful coincidences in everyday life shared on TwitterMicro-serendipity: Meaningful coincidences in everyday life shared on Twitter
Micro-serendipity: Meaningful coincidences in everyday life shared on Twitter
 
Bibliotek 2.0, brugspotentialer og brugerinvolvering
Bibliotek 2.0, brugspotentialer og brugerinvolveringBibliotek 2.0, brugspotentialer og brugerinvolvering
Bibliotek 2.0, brugspotentialer og brugerinvolvering
 
Web 2.0, brugerinvolvering og sociale teknologier
Web 2.0, brugerinvolvering og sociale teknologierWeb 2.0, brugerinvolvering og sociale teknologier
Web 2.0, brugerinvolvering og sociale teknologier
 
Serendipitet og brugerskabt formidling
Serendipitet og brugerskabt formidlingSerendipitet og brugerskabt formidling
Serendipitet og brugerskabt formidling
 
På sporet efter hinanden - Web 2.0 og social navigation
På sporet efter hinanden - Web 2.0 og social navigationPå sporet efter hinanden - Web 2.0 og social navigation
På sporet efter hinanden - Web 2.0 og social navigation
 

Recently uploaded

The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxGaneshChakor2
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfMahmoud M. Sallam
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application ) Sakshi Ghasle
 
Biting mechanism of poisonous snakes.pdf
Biting mechanism of poisonous snakes.pdfBiting mechanism of poisonous snakes.pdf
Biting mechanism of poisonous snakes.pdfadityarao40181
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon AUnboundStockton
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Celine George
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxAvyJaneVismanos
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonJericReyAuditor
 
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxEPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxRaymartEstabillo3
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17Celine George
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
Blooming Together_ Growing a Community Garden Worksheet.docx
Blooming Together_ Growing a Community Garden Worksheet.docxBlooming Together_ Growing a Community Garden Worksheet.docx
Blooming Together_ Growing a Community Garden Worksheet.docxUnboundStockton
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionSafetyChain Software
 

Recently uploaded (20)

Staff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSDStaff of Color (SOC) Retention Efforts DDSD
Staff of Color (SOC) Retention Efforts DDSD
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
CARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptxCARE OF CHILD IN INCUBATOR..........pptx
CARE OF CHILD IN INCUBATOR..........pptx
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
 
Hybridoma Technology ( Production , Purification , and Application )
Hybridoma Technology  ( Production , Purification , and Application  ) Hybridoma Technology  ( Production , Purification , and Application  )
Hybridoma Technology ( Production , Purification , and Application )
 
Biting mechanism of poisonous snakes.pdf
Biting mechanism of poisonous snakes.pdfBiting mechanism of poisonous snakes.pdf
Biting mechanism of poisonous snakes.pdf
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
 
Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17Computed Fields and api Depends in the Odoo 17
Computed Fields and api Depends in the Odoo 17
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptx
 
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Science lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lessonScience lesson Moon for 4th quarter lesson
Science lesson Moon for 4th quarter lesson
 
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptxEPANDING THE CONTENT OF AN OUTLINE using notes.pptx
EPANDING THE CONTENT OF AN OUTLINE using notes.pptx
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17How to Configure Email Server in Odoo 17
How to Configure Email Server in Odoo 17
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
Blooming Together_ Growing a Community Garden Worksheet.docx
Blooming Together_ Growing a Community Garden Worksheet.docxBlooming Together_ Growing a Community Garden Worksheet.docx
Blooming Together_ Growing a Community Garden Worksheet.docx
 
Mastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory InspectionMastering the Unannounced Regulatory Inspection
Mastering the Unannounced Regulatory Inspection
 

Webometrics 1.0 from AltaVista to Small Worlds and Genre Drift

  • 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
  • 2.
  • 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
  • 6.
  • 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)
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 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)
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 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)
  • 30.
  • 31.
  • 32.
  • 33.
  • 36. web of genres genre network graph extracted with Pajek software © Björneborn
  • 37.
  • 38.
  • 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 .