Link analysis as a social science technique
Mike Thelwall
Statistical Cybermetrics Research Group
University of Wolverhampton, UK
http://cybermetrics.wlv.ac.uk/
Link Analysis Manifesto Links are:
A wonderful new source of information about relationships between people, organisations and information
An easy to collect data source But:
Results should be interpreted with care
Talk Structure Part 1: Academic link analysis –mainly
from an information science perspective Part 2: Software demonstration Part 3: A social science link analysis
methodology
Link Analysis: Motivation Individual hyperlinks reflect concrete creation
reasons such as connections between web page contents or creators
Counts of large numbers of hyperlinks may reflect wider underlying social processes
Links may reflect phenomena that have previously been difficult to study, opening up new research areas E.g. informal scholarly communication
Part 1: Academic Hyperlink Analysis 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
Data Collection Web crawler AltaVista advanced queries, e.g. Links from
Wolves Uni. to Oxford Uni.domain:wlv.ac.uk AND linkdomain:ox.ac.uk Google link queries
Find links to specific URLs, e.g. links to the Institute home page
link:www.oii.ox.ac.uk
Types of link count
Direct link counts Inter-site links only
Co-inlink counts B and C are co-inlinked
Co-outlink counts D and E are co-outlinked
B C
A D E
F
Alternative Document Models A method to ignore multiple similar links
E.g., domain ADM: count links between domains instead of pages
P1P2P3
P4P5P6
www.scit.wlv.ac.uk www.oii.ox.ac.uk
Some Inter-University Hyperlink Patterns
Mainly for the UK and Europe
Citation-Style 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
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
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
Universities tend to link to neighbours
Universitiesclustergeographically
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}
Can map patterns of international communicationCounts of links between EU universities in Swedish are represented by arrow thickness.
Counts of links between EU universities in French are represented by arrow thickness.
Which language???
Which language???
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
The next slide is a (Kamada-Kawai) network of the interlinking of the “top” 5 universities in AEAN countries (Asia and Europe) with arrows representing at least 100 links and universities not connected removed.
(Research with Han Woo Park)
Clustering using links
Background: Power laws in Academic Webs
Academic Webs have a topology dominated by power laws, including Counts of links to pages (inlink counts) Counts of links to pages (outlink counts) Groups of interconnected pages
Power laws mean that Link creation obeys the ‘rich get richer’ law “Communities” of pages or sites are rarely pure but
tend to multiply overlap
Page Outlinks
Topological component sizes: “pure link communities”
Community Identification Algorithm: “Impure communities”
Can apply to pages, directories and domains Gives complimentary results: a “layered
approach”
1
10
100
1000
10000
1 10 100 1000 10000
Community size: Directory model, k = 32
Freq
uenc
y
1
10
100
1000
10000
100000
1 10 100 1000 10000 100000
Community size: page model, k = 32
Freq
uenc
y
Stretching links further: co-inlinks, co-outlinks More interlinked does not imply more similar
For the UK academic Web, about 42% of domains connected by links alone host similar disciplines, and about 43% connected by links, co-inlinks and co-outlinks
Can use any type of link to look for similar sites Over 100 times more domains are co-inlinked or co-
outlinked than are directly linked Links in any form are less than 50% reliable as
indicators of subject similarity
Summary Studies of the relatively restricted
subdomain of university web sites Produce direct research results
For Web Information Retrieval (e.g. search engines), they also Help refine methodologies Help build intuition about web structure
Part 2: Software Demonstration SocSciBot
Web crawler for social sciences research
SocSciBot Tools Link analyser for SocSciBot data
Cyclist Search engine with some corpus linguistics capability
(e.g. word frequency lists for each site)
http://socscibot.wlv.ac.uk/
Part 3: A General Social Science Link Analysis Methodology A general framework for using link counts in
social sciences research For research into link creation or Together with other sources, for research into other
online or offline phenomena Applicable when there are enough links relevant
to the research question to count For collections of large web sites or For large collections of small web sites
Nine stages for a research project1. Formulate an appropriate research
question, taking into account existing knowledge of web structure
2. Conduct a pilot study
3. Identify web pages or sites that are appropriate to address the research question
Nine stages for a research project4. Collect link data from a commercial
search engine or a personal crawler, taking appropriate accuracy safeguards
5. Apply data cleansing techniques to the links, if possible, and select an appropriate counting method
6. Partially validate the link count results through correlation tests, if possible
Nine stages for a research project7. Partially validate the interpretation of the results
through a link classification exercise
8. Report results with an interpretation consistent with link classification exercise, including either a detailed description of the classification or exemplars to illustrate the categories
9. Report the limitations of the study and parameters used in data collection and processing
Interpreting link counts For most research, need to be able to place an
interpretation on link counts E.g. A links to B more than C, therefore… A is inlinked more than B therefore…
Do links ‘measure’ visibility, luminosity, authority, information exports/imports, communication, impact, online impact, quality, importance, interpersonal communication, nothing, random actions,…?
Interpreting link counts Classifying random samples of links can
help decide how to interpret them E.g. Links predominantly reflect…
Correlation test are also useful as a form of triangulation E.g. Links counts associate with…
The theoretical perspective for link counting In order to be able to reliably interpret link
counts, all links should be created individually and independently, by humans, through equivalent gravity judgments (e.g., about the
quality of the information in the target page). Additionally, links to a site should target pages
created by the site owner or somebody else closely associated with the site.
Summary Link counts are an information source that
may reveal new insights into online and offline phenomena
Can be used in conjunction with other data sources to address many research questions
With existing tools, are relatively easy to use in research