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www.sciencemag.org SCIENCE VOL 294 30 NOVEMBER 2001 1849
tor that considerably
enhances TCR-mediat-
ed responses. The CD8
complex of these cells
is a heterodimer com-
prising CD8α and
CD8β chains. This het-
erodimer interacts with
classical major histo-
compatibility (MHC)
class I molecules, which
are expressed by virtu-
ally all cells in the
body. These MHC class
I molecules present
antigenic peptides to
CD8αβ T cells. Most
IELs, however, express
a different CD8 com-
plex—a CD8αα ho-
modimer composed of
two α chains. Leish-
man et al. demonstrate
a high-affinity interac-
tion between the CD8αα
homodimer and an un-
usual (nonclassical)
MHC class I molecule
called thymus leukemia
antigen (TL). The TL
molecule has two inter-
esting characteristics: It
does not present anti-
genic peptides (in con-
trast to its classical MHC class I relatives),
and it is expressed almost exclusively by
epithelial cells of the small intestine (7).
Strong interactions between CD8αα and
TL enable IELs to interact directly and lo-
cally with the gut epithelium, but indepen-
dently of antigen recognition and TCR
specificity.
What are the consequences of this in-
teraction? Leishman et al. (2) compared
IEL responses to antigen-presenting cells
that did or did not express the TL
molecule (see the figure). Surprisingly,
they found that CD8αα-TL interactions
could either enhance or suppress IEL re-
sponses. Such interactions considerably
enhance cytokine release by IELs but in-
hibit their proliferation and cytotoxicity.
These apparently paradoxical effects make
a lot of sense in the particular environment
of the small intestine. By inhibiting prolif-
eration, CD8αα-TL interactions prevent
IELs from dividing and disrupting the gut
epithelium. In addition, by blocking T cell
killer activity, these interactions prevent
the elimination of healthy epithelium by
self-reactive IELs (2). In contrast, by fa-
voring interferon-γ production, the binding
of CD8αα to TL may promote turnover of
gut epithelium (1).
These results indicate that the small in-
testine and IELs have developed a unique
way to control local homeostasis and to
ensure continuous epithelial cell renewal.
The mechanisms by which CD8αα-TL in-
teractions induce such paradoxical effects
on IEL responses remain to be discovered.
Hints may come from certain types of in-
flammatory bowel disease that are associ-
ated with a deficiency in regulatory T lym-
phocytes, or overproduction of the inflam-
matory cytokine interleukin-10 (8). It is
possible that in these disorders there is a
severing of the interaction between
CD8αα and TL. If so, then these diseases
may yield valuable information about the
maintenance of gut homeostasis.
References
1. D. Guy-Grand et al., Eur. J. Immunol. 28, 730 (1998).
2. A. J. Leishman et al., Science 294, 1936 (2001).
3. H. Saito et al., Science 280, 275 (1998).
4. B. Rocha, P. Vassalli, D. Guy-Grand, J. Exp. Med. 173,
483 (1991).
5. B. Rocha, H. von Boehmer, D. Guy-Grand, Proc. Natl.
Acad. Sci. U.S.A. 89, 5336 (1992).
6. D. Masopust, V. Vezys, A. L. Marzo, L. Lefrancois, Sci-
ence 291, 2413 (2001).
7. R. Hershberg et al., Proc. Natl. Acad. Sci. U.S.A. 87,
9727 (1990).
8. K. J. Maloy, F. Powrie, Nature Immunol. 2, 816 (2001).
C
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E
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IT
S
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)
I
n the span of a decade, the World Wide
Web has grown from a small research
project into a vast repository of infor-
mation and a new medium of communica-
tion. Unlike other great networks of the
past century—such as the electric power
grid, the telephone system, or the highway
and rail systems—the Web does not have
an engineered architecture. Rather, it is a
virtual network of content and hyperlinks,
with over a billion interlinked “pages” cre-
ated by the uncoordinated actions of tens
of millions of individuals.
Because of the decentralized nature of
its growth, the Web has been widely be-
lieved to lack structure and organization as
a whole. Recent research, however, shows
a great deal of self-organization. Analyses
of the Web’s network of hyperlinks have
revealed an intricate structure that is prov-
ing to be valuable for organizing informa-
tion, improving search methods, and un-
derstanding the Web in a broader techno-
logical and social context.
A recent study (1) indicates that the
Web contains a large, strongly connected
core in which every page can reach every
other by a path of hyperlinks. This core
contains most of the prominent sites on
the Web. The remaining pages can be
characterized by their relation to the core:
Upstream nodes can reach the core but
cannot be reached from it, downstream
nodes can be reached from the core but
cannot reach it, and “tendrils” contain
nodes that can neither reach nor be
reached from the core.
In fairly large snapshots of the Web,
these four components—core, upstream,
downstream, and tendril regions—have
roughly comparable sizes. Moreover, the
core is very compact: The shortest path
from one page in the core to another in-
volves 16 to 20 links on average, a “small-
world” situation in which typical distances
P E R S P E C T I V E S : N E T W O R K A N A LY S I S
The Structure of the Web
Jon Kleinberg and Steve Lawrence
J. Kleinberg is in the Department of Computer Sci-
ence, Cornell University, Ithaca, NY 14853, USA. E-
mail: kleinber@cs.cornell.edu S. Lawrence is in the
NEC Research Institute, Princeton, NJ 08540, USA. E-
mail: lawrence@research.nj.nec.com
CD8ααCD8αα TL
Low
cytokine
High
cytokine
APC
TCR
Antigen
MHC class 1
Proliferation
Intestinal epithelium
IEL IEL
APC killing No APC killing
No proliferation
TL death us do part. Interactions between CD8αα and TL regulate the
behavior of intraepithelial lymphocytes (IELs). Epithelial cells of the
small intestine (yellow) express the TL molecule and are overlaid by a
layer of mucus (pink). IELs (blue), localized among the gut epithelial
cells, express CD8αα (red). (Bottom, left) If isolated IELs are stimulat-
ed by antigen-presenting cells (APCs) that express antigen but lack TL,
they divide and kill target cells but secrete low amounts of cytokines.
(Bottom, right) If APCs express both antigen and TL, IELs secrete high
amounts of cytokines but do not divide and do not kill target cells.
S C I E N C E ’ S C O M P A S S
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30 NOVEMBER 2001 VOL 294 SCIENCE www.sciencemag.org1850
are very small relative to the overall size
of the system (1–4).
Also at a global level, studies have ana-
lyzed the distribution of hyperlinks among
pages. Several studies have shown that the
number of links to and from individual
pages is distributed according to a power
law over many orders of magnitude (1, 5,
6); the fraction of pages with n in-links is
roughly n–α for α ~ 2.1.
If the processes that drive
Web growth are highly decen-
tralized, then the power law
must arise from a composite of
local behavior. An appealing
proposal, suggested indepen-
dently in different forms (5, 7,
8), is the mechanism of prefer-
ential attachment. In this ran-
domized, “rich-get-richer” pro-
cess, the network grows by the
sequential arrival of new nodes,
and the probability that an ex-
isting node gains a link is pro-
portional to the number of links
it currently has. The result is a
power law distribution of links.
It is thus plausible for a
power law to arise through a
simple mechanism. Neverthe-
less, we are far from a complete
understanding of the processes governing
Web growth. Deviations from power-law
scaling occur, especially at small numbers
of links (1). Furthermore, the deviation
varies for different categories of pages (9).
For example, the distribution of links to
university home pages diverges strongly
from a power law, following a far more uni-
form distribution. Recent models seek to
improve on the accuracy of the original
preferential attachment models (9, 10).
At a local level—the scale of small
neighborhoods and focused regions of the
Web—the structure turns out to be even
more intricate and quite nonuniform.
Pages and links are created by users with
particular interests, and pages on the same
topic tend to cluster into natural “commu-
nity” structures that exhibit an increased
density of links.
Turning this observation around leads
to a powerful method for analyzing the
content of the Web. An unusually high
density of links among a small set of pages
is an indication that they may be topically
related. A characteristic pattern in such
communities consists of a collection of
“hub” pages—guides and resource lists—
linking in a correlated fashion to a collec-
tion of “authorities” on a common topic
(see the left panel in the figure) (11). A re-
lated pattern is one in which authorities on
a topic link directly to other authorities,
again creating a density of links (12).
Link analysis as a means of finding au-
thoritative, relevant sources on the Web
has proven useful in the design of im-
proved search engines (12, 13). This appli-
cation of link analysis has clear connec-
tions with, as well as interesting contrasts
to, citation analysis of scientific literature
and the identification of “central” individ-
uals in a social network (3, 11, 14).
Knowing the characteristic link structures
that identify Web communities, one can ex-
amine a large snapshot of the Web for all oc-
currences of the link-based “signature” of a
community. Using a signature corresponding
to an interlinked collection of hubs and au-
thorities, one large-scale study found over
100,000 coherent community structures; es-
timates based on sampling suggested that the
overwhelming majority covered focused top-
ics (6). The list included communities not
considered by the creators of popular Web
portals (for example, a community of people
concerned with oil spills off the coast of
Japan), showing that analysis of the Web’s
structure can help to define topics and social
groupings of interest to its denizens.
A community can also be defined as a
collection of pages in which each member
page has more links to pages within the
community than to pages outside the com-
munity (see the right panel in the figure)
(15). This definition may be naturally ex-
tended to identify communities with varying
levels of cohesiveness. Communities defined
in this way are closely related to network
flow computations, a powerful combinatorial
technique designed for graph partitioning
problems. As with the previous approach,
this method of searching for communities re-
veals a remarkable degree of self-organiza-
tion in the Web’s link structure, and textual
analysis of the communities shows that the
constituent pages are topically related.
Analysis of the Web’s structure is lead-
ing to improved methods for accessing and
understanding the available information,
for example, through the design of better
search engines, automatically compiled di-
rectories, focused search services, and
content f iltering tools. Although re-
searchers have been surprised at what can
be discovered based solely on the structure
of the Web, the integration of link- and
content-based analysis will typically im-
prove upon either method alone. Beyond
these applications, the appearance of an
increasing fraction of human knowledge
and communication on the Web offers an
unprecedented opportunity for charting
and analyzing interests and relationships
within society, as reflected in the Web’s
content and hyperlinks.
The migration of communication and
commerce to the Web is also altering in-
formation flow in the world. We are only
beginning to understand how link structure
affects the visibility of Web sites. New or
niche sites with few links to them may
have diff iculty competing with highly
prominent sites for attention. By favoring
more highly linked sites, search tools may
increase this effect. But deeper analysis,
exposing the structure of communities em-
bedded in the Web, raises the prospect of
bringing together individuals with com-
mon interests and lowering barriers to
communication.
References and Notes
1. A. Broder et al., in Proceedings of the Ninth Interna-
tional World Wide Web Conference (Elsevier, Ams-
terdam, 2000), pp. 309–320.
2. R. Albert, H. Jeong, A.-L. Barabási, Nature 401, 130
(1999).
3. S. Wasserman, K. Faust, Social Network Analysis
(Cambridge Univ. Press, Cambridge, 1994).
4. D. Watts, S. Strogatz, Nature 393, 440 (1998).
5. A.-L. Barabási, R. Albert, Science 286, 509 (1999).
6. R. Kumar, P. Raghavan, S. Rajagopalan, A. Tomkins, in
Proceedings of the Eighth International World Wide
Web Conference (Elsevier, Amsterdam, 1999), pp.
403–415.
7. B. Huberman, L. Adamic, Nature 401, 131 (1999).
8. R. Kumar, P. Raghavan, S. Rajagopalan, A. Tomkins, in
Proceedings of the IEEE Symposium on Foundations
of Computer Science (IEEE Computer Society Press,
Los Alamitos, CA, 2000), pp. 57–65.
9. D. M. Pennock, C. L. Giles, G. W. Flake, S. Lawrence, E.
Glover, Winners Don’t Take All: A Model of Web Link
Accumulation (Technical Report 2000-164, NEC Re-
search Institute, Princeton, NJ, 2000).
10. R. Albert, A.-L. Barabási, Phys. Rev. Lett. 85, 5234
(2000).
11. J. Kleinberg, in Proceedings ACM-SIAM Symposium
on Discrete Algorithms (ACM-SIAM, New York/
Philadelphia, 1998), pp. 668–677.
12. S. Brin, L. Page, in Proceedings of the Seventh Interna-
tional World Wide Web Conference (Elsevier, Ams-
terdam, 1998), pp. 107–117.
13. S. Chakrabarti et al., IEEE Computer 32, 60 (1999).
14. L. Egghe, R. Rousseau, Introduction to Informetrics
(Elsevier, Amsterdam, 1990).
15. G. W. Flake, S. Lawrence, C. L. Giles, F. Coetzee, IEEE
Computer, in press.
16. J. K. is supported in part by grants from the NSF, the
Office of Naval Research, and the Packard Foundation.
S C I E N C E ’ S C O M P A S S
Hubs
Authorities
How is the Web organized? (Left) Web pages can be de-
fined as hubs and authorities. A hub is a page that points to
many authorities, whereas an authority is a page that is
pointed to by many hubs (11). Characteristic patterns of
hubs and authorities can be used to identify communities of
pages on the same topic. (Right) An alternate method for
identifying communities seeks a set of nodes for which the
link density is greater among members than between mem-
bers and the rest of the network (15).
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http://science.sciencemag.org/
The Structure of the Web
Jon Kleinberg and Steve Lawrence
DOI: 10.1126/science.1067014
(5548), 1849-1850.294Science
ARTICLE TOOLS http://science.sciencemag.org/content/294/5548/1849
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