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Using a psychotechnological perspective, this study discusses the current model of information ranking by search engines, based on quantitative Web Popularity (WP), which binds users to a cognitive adaptation to the rank-system restrictions. This phenomenon gives rise to a “rich-get-richer” effect on the Web. This paper claims that such an effect could be limited or reversed by the introduction of quality factors in ranking, and addresses the case of accessibility as a fundamental such factor. A study is reported which, through introducing an accessibility factor in a well-known popularity ranking algorithm, demonstrates that this transformation allows a qualitative rearrangement, without modifying or weighing on the properties of the rank. The overall approach is grounded on two development factors: the analysis of accessibility through specific tools and the employment of this analysis within all components used to build up the ranking. The results show that it is important to reconsider WP as including not only on the number of inbound and outbound links of a website, but also on its level of accessibility for all users, and on users’ judgment of the website use as efficient, effective, and satisfactory.
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LONG PAPER
Web popularity: an illusory perception of a qualitative order in
information
Stefano Federici Simone Borsci Maria Laura Mele
Gianluca Stamerra
Published online: 10 February 2010
Springer-Verlag 2010
Abstract Using a psychotechnological perspective, this
study discusses the current model of information ranking
by search engines, based on quantitative Web Popularity
(WP), which binds users to a cognitive adaptation to the
rank-system restrictions. This phenomenon gives rise to a
‘‘ rich-get-richer’ effect on the Web. This paper claims that
such an effect could be limited or reversed by the intro-
duction of quality factors in ranking, and addresses the case
of accessibility as a fundamental such factor. A study is
reported which, through introducing an accessibility factor
in a well-known popularity ranking algorithm, demon-
strates that this transformation allows a qualitative rear-
rangement, without modifying or weighing on the
properties of the rank. The overall approach is grounded on
two development factors: the analysis of accessibility
through specific tools and the employment of this analysis
within all components used to build up the ranking. The
results show that it is important to reconsider WP as
including not only on the number of inbound and outbound
links of a website, but also on its level of accessibility for
all users, and on users’ judgment of the website use as
efficient, effective, and satisfactory.
Keywords Accessibility Ranking model
Web popularity Human computer interaction
1 Introduction
The development of the Internet, even though the ‘‘digital
divide’’ problems still must be resolved, is entering into a
new phase centered on the relationship between users and
technology. All kinds of technology can be described as an
amplifier [1] which transports rules, restrictions and
knowledge possibilities. But forces users to a cognitive and
cultural adaptation.
Website Popularity (WP) appeared in the 1990s as a
quantitative indicator in response to the need of order
search engines’ results by organizing web information into
‘classifications’’ able to answer to users’ queries [2]. Such
classifications express the WP in orders of value (rank).
The term ‘‘popularity’’ has to be understood as ‘‘wide
popular consent’’, calculated in number of websites visits.
At the beginning of web technology development, this
formulation has been useful, but it has soon assumed an
implied qualitative meaning, concerning the quality and
accessibility of website of content. The rank order as an
index of quality could be acceptable only if search engines
contained in their algorithms factors connected to the
structural quality of websites and their information, which
however does not hold. Therefore, the consent on which
WP is measured by search engines does not consider the
users’ judgement about website content and quality.
However, WP rank implicitly indicates a quality level
concerning the website, simply because, as on the market
the most a good is sold, the better the good, in the case of
the web, the most a website is clicked, the better the
website.
The abstract of this article is also presented in the 4th Biennial
Disability Studies Conference at Lancaster University,
UK 2nd–4th September 2008.
S. Federici (&)
Department of Human and Educational Sciences,
University of Perugia, Perugia, Italy
e-mail: stefano.federici@unipg.it
S. Federici S. Borsci M. L. Mele G. Stamerra
ECoNA, Interuniversity Center for Research in Cognitive
Processing in Natural and Artificial Systems,
Univeristy of Rome ‘‘La Sapienza’’, Rome, Italy
123
Univ Access Inf Soc (2010) 9:375–386
DOI 10.1007/s10209-009-0179-7
Search engines order any query outputs in a top–down
hierarchical sequence, starting from the greatest ranking
level website to the lowest. So the highest website occur-
ring in the rank is perceived by users as qualitatively better
than others, i.e., as the best answer to the users’ queries. In
this way, it has become a common idea that search engines
and ranking lists are structured to offer as fast as possible
the best answer to the users’ queries. A certain ‘‘cognitive
consonance’’, according to which websites with best rank
value have the best content quality (i.e., demand met
supply), has produced a circular and vicious process: since
popular websites are already better reachable in the virtual
space (that meaning they will probabilistically get more
clicks), they will always be more popular [3,4]. Since they
appear in the first rank positions, popular websites are more
likely to be clicked, and this influences both users’ choices
and information use. In this way, quality becomes a mere
technological product that informs and forms the users’
reality, influencing their judgements and choices.
2 Overlap of web popularity and link popularity
measures
Google
TM
’s founders, Brin and Page [5], stress that Internet
ranking is based on ‘‘link popularity’’ (LP), calculated on
the base of ‘‘inbound’’ and ‘‘outbound’’ number of links.
The more links leading to a certain website, the higher rank
position in the search engines that website has. Though it is
known that also other ranking factors are included in
Google
TM
’s algorithm, such as the ‘‘dumping’’ factor (i.e.,
the rank value of a single webpage) and the website traffic,
it is undeniable that currently WP is primarily determined
by LP, and it is commonly believed that websites’ quality
and popularity are directly related through the number of
links [6]. In the most used search engines, Google.com,
Yahoo.com and Msn.com [7], searching the keywords
‘link popularity’’ and ‘‘website popularity’’ (synonymous
are: ‘‘web site popularity’’, ‘‘web popularity’’ and ‘‘popu-
larity’’) will obtain a near coincidence of the first 10 results
(see Table 1).
Popularity rank is certainly the main criterion used by
search engines both to arrange web information and to
reply to users’ queries with effectiveness and efficiency [8].
Yet, this functional order criterion can be misunderstood
when users assume that the highest websites in the rank
offer better content quality than others.
The ranking algorithms should be elaborated consider-
ing the users’ judgements on visited pages in order to
introduce a quality factor in the WP index.
Thomson Scientific ‘‘Impact factor’’ (IF) index provides
an example illustrating the difference between a quantita-
tive and a qualitative rank (http://scientific.thomson.com/
index.html). IF consists of a value assigned to each journal
listed in the Citation index (a scientific journals and articles
collection), which is calculated over a 3-years period. It
consists in the ratio between the numbers of citations of the
papers published in a specific journal within a year’s per-
iod, and the total amount of papers published by the same
journal in the last 2 years [9,10]. Therefore, IF quantita-
tively expresses the impact of a journal in the scientific
community, intended as quantity of readers and citations.
In this particular case the quantitative value of scientific
journals popularity could represent an index for scientific
content quality (at least for the scientific community using
Citation Indexes as a popularity index). Therefore, the
‘popularity’’ index (given by the IF) expresses how many
times an article has been used by the users’ community,
and in this way it guarantees the information ranking sys-
tem’s external quality (Thomson Scientific).
The WP produced by search engines does not consider
users’ judgement about websites’ content: it only computes
the number of links and the website traffic quantity.
Both these kinds of rank (WP and IF) could suffer from
a vicious cycle. Explaining success in scientific publica-
tion, Merton [11,12] shows that popularity is a cumulative
process; in fact well known scientists get disproportion-
ately great credit for their contributions to science, while
relatively unknown scientists tend to get disproportionately
little credit for comparable contributions (Matthew Effect).
IF, contrary to WP, is based on a participative and delib-
erate popularity. At the same time, as Merton shows, even
popularity in the scientific community is linked to factors
different from pure quality, but it should be considered that
a scientific reader is more aware of this influenced ranking
process than a web user, who is forced to a simple clicking
automatism.
Table 1 Results using the queries ‘‘Link Popularity’’ and ‘‘Website Popularity’’ in three different search engines
Search engines WP total results LP total results First Serp
Google.com 65.300.000 16.800.000 9/10 Relation between LP/WP
Yahoo.com 77.100.000 64.600.000 8/10 Relation between LP/WP
Msn.com 27.900.000 20.500.000 9/10 Relation between LP/WP
WP web popularity, LP link popularity, SERP search engines results page
376 Univ Access Inf Soc (2010) 9:375–386
123
The actual ranking algorithms used by search engines
lead to the impossibility for not popular websites to emerge
from the web. As Cho et al. [2] show, the ‘‘rich-get-richer’
phenomenon is widespread through the web: the popularity
of already popular web pages tends to increase, while the
new or not popular pages have less possibilities to be
clicked.
However, some empirical studies seem to reject the
passive view of web users as subjects unaware of the ‘‘rich-
get-richer’’ induced phenomenon.
Fortunato et al. [4] show that a users’ adaptive behav-
iour exists that mitigates WP incidence as a ranking factor.
In fact, expert users tend to extend their searches from most
to less popular websites, thus producing a redistribution of
the web traffic (Mitigation Effect). In addition, the same
study shows that over a certain number of in-links, a
website does not increase its WP and visibility in the rank
(Saturation Effect). These two effects (Mitigation and
Saturation Effect) depend on the users’ interest for the
searched subject: once users have visited the most popular
websites concerning their interest, then they will move to
less popular ones, thus redistributing Internet traffic.
However, this redistribution depends mostly on users’
expertise in finding information and extending their search
to less popular websites, whereas less expert users are often
stopped by online barriers and therefore they cannot con-
tribute to Internet traffic redistribution. In this way, expert
users’ behaviour mitigate the quantitative WP. These users,
having developed an adaptation to the limits of the search
engine results page (SERP), can access peripheral and
higher quality information. On the other hand, the rank and
information distribution structured by quantitative popu-
larity becomes a barrier for novice or not so expert users.
The possibilities of web access remain unequal and tend to
extend the digital divide. As all technologies, the world
wide web forces all its users to an adaptation, but such a
process could be simplified by modifying the ranking
algorithms with a qualitative index that could expand the
current WP formulation.
A quality index, inserted in the search engines’ algo-
rithms, could produce a more user-centered information
availability process, which would still allow information
ranking, and at the same time would guarantee accessibility
to better quality information for all Internet users, inde-
pendently from their technological skills.
A first qualitative aspect that should be imported in the
WP is website accessibility, defined as: ‘‘The art of
ensuring that, to as large an extent as possible, facilities are
available to people whether or not they have impairments
of one sort or another’’ [13]. Accessibility constitutes the
first fundamental level of information access, even though
it still does not guarantee content quality to users. A pop-
ularity index including this factor could constitute a
significant step towards universal access, through reducing
the users’ cognitive workload in web navigation, and thus
allowing a easier fruition of web contents. Adding the
accessibility factor to the ranking process can represent a
first step towards the solution of the WP and LP overlap.
2.1 How to overcome the WP and LP overlap
Several international studies on ranking show that:
1. Websites rank positions are stable over Internet history
and development, suggesting that WP may be a
universal Internet property [14].
2. Most popular websites tend to maintain their rank
positions, increasing the discrepancy with less popular
websites.
These studies, targeted to implementing or modifying
ranking metrics, are based on different points of view on
popularity:
Cho et al. [3] proposes a view of WP as quality of a
single page derived from a hypothetical user model,
with the objective to overcome the ‘‘rich-get-richer’
phenomenon. It is also proposed to integrate into the
rank algorithm a new function, named ‘‘pagequality’’,
introducing in the popularity rank computation a factor
derived by the hypothetical user model. Even though
this seems an interesting solution, it appears to be
external to search engines’ algorithms and too much
dependent on the limits of a generic hypothetical user
model. In fact, the actual necessity is to find an
evaluation process that could be integrated in the
ranking metrics used by search engines.
Nie et al. [15] propose to integrate WP with the quality
of links, instead of quantity of links. An ‘‘object
ranking’ model is proposed, named PopRank (popu-
larity rank), that considers every link present on a
webpage as an object having a specific weight. In this
way, the PopRank model allows a diversification of
popularity ranks, since every link has a different weight
and therefore a different influence. This solution,
though, cannot be considered as a universal quality
index, since it is not able to overcome the vicious
relationship between WP and LP.
More recently, Yen [16] proposes to integrate WP with
page design. From this point of view, WP is understood
as the easiness degree with which a page is able to be
found across other pages and links (findability). Such
formulation is based on a point of view dependent on the
quantitative popularity according to which the accessi-
bility, here understood as findability, is strictly related
with the number of links (i.e., more a website is linked
by other websites more is findable in the search engines
Univ Access Inf Soc (2010) 9:375–386 377
123
and accessible). In this sense, findability can be defined
as quantitative accessibility. This approach is useful to
create calibrated web structures, where the pages with
the most important content should have the highest in-
links number from other websites; in this way, there
should be a connection between popularity and pages
with the most remarkable information. This model,
though useful for building easily findable and calibrated
web structures, does not succeed in overcoming the
quantitative logic and it remains dependent on web
design analysis, without considering web accessibility
in its most shared meaning: ‘‘that people with disabil-
ities can perceive, understand, navigate, and interact
with the Web, and that they can contribute to the Web
(http://www.w3.org/WAI/intro/accessibility.php).
Signore [17] assumes that the quality of websites is
often unsatisfactory, and designers ignore or scarcely
consider basic web principles, such as interoperability
and accessibility. In order to automatically evaluate a
website, Signore proposes a quality model based on five
dimensions: correctness, presentation, content, naviga-
tion, and interaction. This point of view is based on the
standard quality characteristics of software [18] and is
targeted to evaluate quality as an objective dimension.
Therefore, in this model, the quality of websites is just
calculated as a relation among those five qualitative
dimensions without taking into account the user’s
judgment.
Zeng and Parmanto [19] show that there is a correlation
between WP and accessibility, the latter being under-
stood as the possibility to guarantee information access
to the largest extent of people, independently from any
kind of disabilities [13]. For their analysis of accessi-
bility, the authors propose an index, named Wabscore
(Web Accessibility Barrier Score), that measures how
many accessibility barriers are present in a website,
calculating the Web Content Accessibility Guideline
1.0 (WCAG) violations for each web page of the site.
See below the Wabscore Formula
WabScore ¼pv nv
Nv

wv
Np
where p: Total pages of a website,
v: Total violations of a web page,
nv: Number of violations,
Nv: Number of potential violations,
Wv: Weight of violations in inverse proportion to WCAG
prority,
Np: Total number of pages checked
Through the rank and accessibility analysis of a repre-
sentative sample composed by 108 health information
websites, Zeng shows a correlation between quality,
accessibility and WP. These results indicate that a corre-
lation does exist between WP and website accessibility, at
least in some search engines’ ranking results; therefore, the
usefulness of introducing the accessibility factor in the
search engines’’ algorithms is confirmed.
All these studies show the need, opportunity and pos-
sibility to overcome the current WP formulation main-
taining its primary function of information organization,
and at the same time introducing qualitative factor into the
search engine report page (SERP) order. The WP could be
rethought as an index that actually offers to users the
possibility of receiving qualitative information about the
content available on the web and useful to their searches; in
order to obtain this result, guaranteeing website accessi-
bility could be sufficient, i.e., guaranteeing the absence of
web accessibility barriers.
According to the Webster’s Dictionary, ‘‘popularity’
has a threefold meaning that well matches the different
meanings of WP emerged in the previous review of the
international studies on ranking. Indeed, the first meaning
concerns the features of what is stated to be popular: ‘‘the
quality or state of being popular [] adapted to common
people’’. In this ‘‘objective’’ sense, popular concerns with
the accessibility structure of information—the intrinsically
condition of an object per se—that is popular because it
does not offer resistance (barriers) to users (i.e. his charm
soon won him popularity). The second meaning of popu-
larity refers to the attitudes or believes of people: ‘‘the state
of being esteemed by people at large [] or pleasing to
common people’’. In this ‘‘subjective’’ sense, popularity
concerns people’s perspective onto the features of objects
(i.e. all children are deemed innocent). This is what can be
traced back to ‘‘usability’’, namely, what is deemed popular
on the web by the users because it is suitable, friendly,
satisfactory. The last popularity meaning concerns the
pursuing of an aim: ‘‘Something which obtains, or is
intended to obtain, the favor of the vulgar [] The act of
courting the favor of the people’’. In this sense, popularity
is not just a feature of an object (accessibility) nor a (user)
self-representation of an object (usability), rather it is the
set goal reached (i.e. the fiction’s success gave her popu-
larity), namely the website wide-spreading, such as, for
example, its ‘‘linkability’’.
Therefore, WP can be defined as a property that it is
attributed to a website when it is well widespread on
Internet by the means of inbound and outbound links
(linkability/link-popularity), the information is accessible
for all users (accessibility), and when users esteem its use
as efficient, effective, and satisfactory (usability) [20].
Since WP is currently only ranked on the LP criteria, the
following section will address the issue of what happens in
a website rank order when accessibility is introduced as a
factor of popularity measurement.
378 Univ Access Inf Soc (2010) 9:375–386
123
3 Introduction of an accessibility criterion in the World
Universities’ Rankings
A study has been conducted to empirically verify that the
introduction of an accessibility index in the ranking for-
mula changes the ranking position of a website, which
currently is calculated only by quantitative factors. In this
study, the Zeng and Parmanto [19] WabScore was applied
to the Webometrics Ranking [WR] of World Universities
(http://www.webometrics.info), created by Cybermetrics
Lab, a research group belonging to the Consejo Superior de
Investigaciones Cientı
´
ficas (CSIC).
WR is obtained as an addition of four different ranks
based on quantitative indexes. It was chosen to use the WR
classification, in its 2007 version, for three main reasons:
first, because it is based on shared search engines’ criteria;
second, for its implicit purpose to overcome search
engines’ ranking limits with the integration of different
indexes for better representing the global quality of uni-
versities’ websites and resources; and third, because the
WR formula has been made public until the 2007 version,
even though this formula is no longer available in its 2008
version. The conducted experiment was intended to verify
if the WR criteria and subsequent rank positions of uni-
versities’ websites were correlated to the accessibility level
of those websites.
3.1 Metrics properties of WR
WR 2007 version is obtained as an addition of four different
ranks (http://www.webometrics.info/methodology.html):
Size (S). Number of pages recovered from four engines:
Google, Yahoo, Live Search and Exalead. For each
engine, results are log-normalised to 1 for the highest
value. Then for each domain, maximum and minimum
results are excluded and every institution is assigned a
rank according to the combined sum.
Visibility (V). The total number of unique external links
received (in-links) by a site can be only confidently
obtained from Yahoo Search, Live Search and Exalead.
For each engine, results are log-normalised to 1 for the
highest value and then combined to generate the rank.
Rich Files (R). After the evaluation of their relevance to
academic and publication activities and considering the
volume of the different file formats, the following were
selected: Adobe Acrobat (.pdf), Adobe PostScript (.ps),
Microsoft Word (.doc) and Microsoft Powerpoint (.ppt).
These data were extracted using Google and merging
the results for each filetype after log-normalising in the
same way as described above.
Scholar (Sc). Google Scholar provides the number of
papers and citations for each academic domain. These
results from the Scholar database represent papers,
reports and other academic items.
It should be considered that, according to the Cyber-
metrics Lab website, the WR 2008 indexes description is
quite different from the 2007 version, but the weight
analysis of each singular rank (Visibility, Size, Rich Files,
Scholar) shows no differences with respect to the older
version. The WR formula, that had been made public, has
now disappeared from the Cybermetrics Lab website.
In the 2007 version, the WR formula was as follows:
WR ¼4VðÞþ2SðÞþRþSc
V: Visibility rank, S: Size rank, R: Rich file rank, Sc:
Google scholar rank.
The WR formula shows how the visibility rank (V),
consisting in the number of external in-links, has a bigger
impact on rank position than all the other three ranks. This
happens in the 2008 version as well, even though the for-
mula is not shown and the authors only provide the per-
centage related to each rank: Rank V has 50% of weight on
WR (therefore has the biggest impact), Rank S 20%, Rank
Rand Rank Sc 15%.
In this way, WR aims to offer to users qualitative
exhaustive information, trying to overcome the limits of a
purely WP based ranking.
3.2 Methods and results
In the conducted analysis, the top 3000 Universities’ web-
sites according to WR were considered. They were classi-
fied, on the basis of their WR value, into 20 classes of 150
websites each. Then, as representative sample of each class,
the following were used: the website with the average WR
value, and the websites with the WR value one point over
and one point under the class standard deviation. In con-
clusion, the final sample, representative of the top 3000
websites, was composed of sixty websites (see Appendix 1).
As Zeng and Parmanto [19] suggest, accessibility was
calculated using Bobby
5.0. Bobby identifies the WCAG
1.0 violations, similarly to A-Prompt, EvalAccess 2.0,
Functional Accessibility Evaluator 1.0, and other validators.
The data obtained were used in order to calculate the
WabScore value for each website. WabScore values range
from 0 (fully accessible website) to 1 (not accessible web-
site), and the sample analysis showed that most of the
websites were not fully accessible. The sample mean was
0.35 (stdv: 0.10), indicating a presence of 35 out of 100
barriers (real or potential).
The analysis did not show any correlation among
WabScore, WR, and the four singular ranks, while it is
clear that all the elements belonging to the four WR ranks
are correlated to WR itself (see Table 2).
Univ Access Inf Soc (2010) 9:375–386 379
123
In conclusion, even though Webometrics Ranking of
World Universities offers a rank based on more analysis
factors than the ones used by search engines, still it does
not consider the accessibility of websites. On the other
hand, as already discussed in this paper, accessibility
should be considered as a decisive factor in a ranking for
websites promoting high level educational content, espe-
cially if they want to guarantee information access to all
users.
Based on the above, it was assumed that it should be
possible to modify a website rank position according to its
accessibility, introducing an accessibility index in the WR.
The WR lists lower values in higher positions, so that the
less is the value of the 4 factors (Visibility, Size, Rich file,
and Google scholar) the higher is the website position rank.
In order to respect the WR properties, the WabScore value
was transformed so that it could be inserted in the WR
calculation as a new rank next to the other four. As Zeng
and Parmanto [19] show, accessibility can be correlated
with WP. In the WR calculation formula, WP is repre-
sented by the Visibility Rank (V).
This relation between V and accessibility gives the
possibility to create an Accessibility Rank (AR) repre-
senting the number of positions that a website should
lessen in the V Rank (i.e., increasing the value in WR
decreasing the rank position) according to its accessibility
problems, as shown in this formula:
VWabScore ¼AR
V:Visibility rank
From this formula a new factor is obtained (the AR, see
Appendix 2) that affects directly the V Rank and indirectly
WR, as proposed in a modification of the WR formula,
named Global Rank (GR) [21]:
GR ¼4VþARðÞðÞþ2SðÞþRþSc
GR: Global Rank, V: Visibility rank, AR Accessibility
Rank, S: Size rank, R: Rich file rank, Sc: Google scholar
rank.
If WabScore is 0, there will no changes in the website
ranking, both in V Rank and WR, since the website is
fully accessible. If WabScore is 1 (that corresponds to
full inaccessibility), the website doubles its value while
lessening the V Rank, and thus influencing the WR
ranking.
Therefore, as far as accessibility is concerned, GR rep-
resents the WR order variation while keeping the correla-
tions with the other ranks unaltered (see Table 3).
The accessibility factor introduced by AR in the GR has
a significant correlation with WabScore and with all the
other WR factors, thus respecting the WR order calculation
properties (see Appendix 3). It is important to notice that
WabScore does not correlate with GR, as well as it does
not correlate with WR (see Wabscore Formula). In this
way, considering accessibility through the AR factor, the
GR does not distort the former WR order: it still correlates
with the other WR factors, while deepening its websites
analysis.
3.3 Suggestions for search engines developers
Based on the proposal presented in this paper, the follow-
ing important issues arise regarding the development of
search engines’ ranking algorithms:
Table 2 Spearman correlations between webometrics factors and
wabscore
S V R Sc WR Wabscore
S 1.000 .801* .764* .689* .909* .113
V .801* 1.000 .674* .621* .927* .135
R .764* .674* 1.000 .729* .833* .160
Sc .689* .621* .729* 1.000 .803* .060
WR .909* .927* .833* .803* 1.000 .107
Wabscore .113 .135 .160 .060 .107 1.000
Ssize rank, Vvisibility rank, Rrich file rank, Sc Google scholar rank,
WR Webometric Rank
* Correlation is significant at the 0.01 level (2-tailed)
Table 3 Spearman correlations between webometrics factors, accessibility rank and global rank
S V R Sc AR Wabscore GR
S 1.000 .801* .764* .689* .756* .113 .894*
V .801* 1.000 .674* .621* .935* .135 .946*
R .764* .674* 1.000 .729* .654* .160 .820*
Sc .689* .621* .729* 1.000 .599* .060 .787*
AR .756* .935* .654* .599* 1.000 .432* .907*
Wabscore .113 .135 .160 .060 .432* 1.000 .160
GR .894* .946* .820* .787* .907* .160 1.000
Ssize rank, Vvisibility rank, Rrich file rank, Sc Google scholar rank, AR accessibility rank, GR WabScore and global rank
* Correlation is significant at the 0.01 level (2-tailed)
380 Univ Access Inf Soc (2010) 9:375–386
123
The integration of some accessibility measurement
formulas in search engines’ algorithms, similar to GR.
If search engines considered an accessibility factor in
their ranking algorithms, website developers would be
more motivated to adopt W3C-WAI accessibility
guidelines in order to grant their own sites’ visibility.
Integrating accessibility in ranking algorithms would be
a first step towards search engines capable of address-
ing web content quality too.
Eventually, as a further step, web interface usability
should be a main goal for future developments of
search engines’ algorithms, introducing user-technol-
ogy interaction quality as a ranking factor.
4 Conclusion
The presented analysis about WP and quality relation on
the Internet has shown how the present LP based search
engines’ algorithms do not suit Internet users’ demands.
Since Internet users are constantly adapting to the tech-
nology, there is a growing need of a qualitative popularity
indexes. As Fortunato et al. show [4], users adapt their
searching strategy to the technology limits, widening their
searches even far from the most popular results, and thus
redistributing web traffic. It is also interesting to consider
how those limits compel users to evolve towards new
adaptive behaviours in complex systems, thus reinforcing
the model of technology as a human action amplifier.
Nevertheless, users adapting to the Internet technology
reproduce the rich-get-richer phenomenon. This situation
can be addressed through the introduction of quality
indexes.
As this paper has shown, the WabScore could be used to
obtain such a quality index, thus allowing rank positioning
reorganization. The modified Webometrics Ranking of
World Universities demonstrates how integrating accessi-
bility in the WP could reorganize rank orders without
altering their properties and goals. In this way, the acces-
sibility diffusion and promotion would be strictly related to
linkability (i.e. like the most popular search-engines do)
plus, at least, to a web quality index (e.g. like our AR
does). Such a link could not only contribute to reduce the
digital divide, but also to downsize the users’ cognitive
workload, thus making it simpler for users to find
information.
Although the WabScore introduces accessibility in the
popularity scoring of the rank, it does not compute the
usability dimension that belongs to the popularity signifi-
cance, as claimed in provided definition of popularity in
accordance with the international literature review (see
Sect. 2.1).
Therefore, future work will be targeted to obtain a WP
rank that encompasses the whole complexity of ‘‘popular-
ity’’, including website spread on Internet by the means of
inbound and outbound links (linkability/LP), information
accessibility for all users (accessibility), and the users’
esteem of the website use as efficient, effective, and sat-
isfactory (usability). Towards this objective, an index also
is currently under development which will weight the
usability of user computer interaction and integrate the
obtained scores with linkability and accessibility.
Appendix
See Tables 4,5,6
Table 4 Sample of websites
Order of
sample
Website S V R Sc WR
1http://www.msu.edu 64 28 26 98 364
2http://www.buffalo.edu 71 71 128 222 776
3http://www.usyd.edu.au 203 111 186 149 1185
4http://www.maine.edu 235 151 74 561 1709
5http://www.uni-ulm.de 132 305 339 269 2092
6http://www.uab.es 265 383 300 118 2480
7http://www.uit.no 258 359 569 519 3040
8http://www.rdg.ac.uk 442 398 418 600 3494
9http://www.utsa.edu 537 433 306 829 3941
10 http://www.mcw.edu 489 351 767 1311 4460
11 http://www.biu.ac.il 627 674 305 612 4867
12 http://www.fordham.edu 1215 159 924 1256 5246
13 http://www.iitb.ac.in 352 1092 403 337 5812
Univ Access Inf Soc (2010) 9:375–386 381
123
Table 4 continued
Order of
sample
Website S V R Sc WR
14 http://www.iisc.ernet.in 628 1036 570 229 6199
15 http://www.gvsu.edu 878 567 848 1741 6613
16 http://www.stevens.edu 1351 663 717 1087 7158
17 http://www.cwu.edu 892 855 713 1602 7519
18 http://www.weber.edu 1060 564 1428 2060 7864
19 http://www.nmu.edu 803 958 791 2183 8412
20 http://www.uniandes.edu.co 1211 1354 686 322 8846
21 http://www.iitk.ac.in 1293 1369 683 530 9275
22 http://www.uevora.pt 587 1619 1114 1083 9847
23 http://www.ttuhsc.edu 1627 830 1530 2087 10191
24 http://www.ulster.ac.uk 1086 1341 1439 1579 10554
25 http://www.niigata-u.ac.jp 1372 1266 2322 890 11020
26 http://www.sciences-po.fr 1951 1108 2238 766 11338
27 http://www.simmons.edu 1737 1002 1776 2340 11598
28 http://www.lcsc.edu 1376 1009 1682 3186 11656
29 http://www.artic.edu 1166 430 4950 3186 12188
30 http://www.bard.edu 2035 983 2753 2266 13021
31 http://www.uhb.fr 1725 1483 2100 2108 13590
32 http://www.uestc.edu.cn 1742 1494 2314 2141 13915
33 http://www.univ-lille2.fr 1803 1968 1533 1247 14258
34 http://www.bvu.edu 1218 1935 2374 2314 14864
35 http://www.bridgeport.edu 2036 1774 1492 2614 15274
36 http://www.ucs.br 1459 2398 1814 1356 15680
37 http://www.nsu.edu 2488 1697 1895 2679 16338
38 http://www.luiss.it 2296 2059 2289 1502 16619
39 http://www.ceu.es 2949 1808 2504 1274 16908
40 http://www.hamk.fi 1056 2468 1760 3701 17445
41 http://www.artcenter.edu 1448 1209 5738 4329 17799
42 http://www.ubu.ac.th 1877 2451 1611 2980 18149
43 http://www.edgewood.edu 2612 1589 2603 4511 18694
44 http://www.savonia-amk.fi 2648 1984 1674 4163 19069
45 http://www.uca.edu.ar 3007 2606 1982 1022 19442
46 http://www.njust.edu.cn 2182 2434 2174 3801 20075
47 http://www.mgimo.ru 2749 2508 2407 2507 20444
48 http://www.dusit.ac.th 2821 2339 1912 3902 20812
49 http://www.sciencespobordeaux.fr 3283 2599 2665 1673 21300
50 http://www.nmhu.edu 3828 2065 1916 3801 21633
51 http://www.xznu.edu.cn 3843 2360 2066 2792 21984
52 http://www.ujn.edu.cn 1581 3298 2646 3531 22531
53 http://www.jct.ac.il 2687 3103 1833 3335 22954
54 http://www.tokai.ac.jp 3075 2177 5189 3335 23382
55 http://www.miem.edu.ru 2181 2880 5095 2893 23870
56 http://www.spc.edu 3338 1779 5678 4707 24177
57 http://www.hebau.edu.cn 2308 3002 2437 5445 24506
58 http://www.rdc.ab.ca 3062 2822 3417 4163 24992
59 http://www.aubg.bg 4069 3203 1573 2824 25347
382 Univ Access Inf Soc (2010) 9:375–386
123
Table 4 continued
Order of
sample
Website S V R Sc WR
60 http://www.ensicaen.fr 2640 3897 2978 1824 25670
The rank order of the sample without any modification (Order of sample), Url (Website), Size rank (S), Visibility rank (V), Rich file rank (R),
Google scholar rank (Sc), Webometric Rank (WR) [chached http://www.webometrics.info, June 2007]
Table 5 Accessibility rank index of websites
Website V Wabscore AR
http://www.msu.edu 28 0.1412294 4
http://www.buffalo.edu 71 0.2889718 21
http://www.usyd.edu.au 111 0.2504605 28
http://www.maine.edu 151 0.298679 45
http://www.fordham.edu 159 0.4138173 66
http://www.uni-ulm.de 305 0.415074 127
http://www.mcw.edu 351 0.5132357 180
http://www.uit.no 359 0.4575269 164
http://www.uab.es 383 0.3624207 139
http://www.rdg.ac.uk 398 0.1242035 49
http://www.artic.edu 430 0.3547774 153
http://www.utsa.edu 433 0.2234849 97
http://www.weber.edu 564 0.3116937 176
http://www.gvsu.edu 567 0.3654671 207
http://www.stevens.edu 663 0.2385974 158
http://www.biu.ac.il 674 0.3625789 244
http://www.ttuhsc.edu 830 0.1409681 117
http://www.cwu.edu 855 0.0813753 70
http://www.nmu.edu 958 0.2952126 283
http://www.bard.edu 983 0.2852888 280
http://www.simmons.edu 1002 0.3676724 368
http://www.lcsc.edu 1009 0.6150826 621
http://www.iisc.ernet.in 1036 0.35242 365
http://www.iitb.ac.in 1092 0.3717004 406
http://www.sciences-po.fr 1108 0.3494034 387
http://www.artcenter.edu 1209 0.3516156 425
http://www.niigata-u.ac.jp 1266 0.4370188 553
http://www.ulster.ac.uk 1341 0.361158 484
http://www.uniandes.edu.co 1354 0.3098967 420
http://www.iitk.ac.in 1369 0.3455658 473
http://www.uhb.fr 1483 0.4025819 597
http://www.uestc.edu.cn 1494 0.3617934 541
http://www.edgewood.edu 1589 0.249702 397
http://www.uevora.pt 1619 0.3171626 513
http://www.nsu.edu 1697 0.3894097 661
http://www.bridgeport.edu 1774 0.4272401 758
http://www.spc.edu 1779 0.3135802 558
http://www.ceu.es 1808 0.3982475 720
http://www.bvu.edu 1935 0.5091097 985
http://www.univ-lille2.fr 1968 0.2203426 434
Univ Access Inf Soc (2010) 9:375–386 383
123
Table 5 continued
Website V Wabscore AR
http://www.savonia-amk.fi 1984 0.33616 667
http://www.luiss.it 2059 0.133901705 276
http://www.nmhu.edu 2065 0.3071112 634
http://www.tokai.ac.jp 2177 0.3519752 766
http://www.dusit.ac.th 2339 0.2994149 700
http://www.xznu.edu.cn 2360 0.3895089 919
http://www.ucs.br 2398 0.5197499 1246
http://www.njust.edu.cn 2434 0.5785757 1408
http://www.ubu.ac.th 2451 0.3007108 737
http://www.hamk.fi 2468 0.2666667 658
http://www.mgimo.ru 2508 0.4081197 1024
http://www.sciencespobordeaux.fr 2599 0.4219648 1097
http://www.uca.edu.ar 2606 0.3890916 1014
http://www.rdc.ab.ca 2822 0.354155329 999
http://www.miem.edu.ru 2880 0.2838405 817
http://www.hebau.edu.cn 3002 0.2732174 820
http://www.jct.ac.il 3103 0.3516174 1091
http://www.aubg.bg 3203 0.3927393 1258
http://www.ujn.edu.cn 3298 0.4380698 1445
http://www.ensicaen.fr 3897 0.2564539 999
The URL (Website), Visibility rank (V), WabScore, Accessibility Rank (AR)
Table 6 Global rank
Old
order
New
order
WebSite S V R Sc WR GR
11 http://www.msu.edu 64 28 26 98 364 380
22 http://www.buffalo.edu 71 71 128 222 776 860
33 http://www.usyd.edu.au 203 111 186 149 1185 1297
44 http://www.maine.edu 235 151 74 561 1709 1889
55 http://www.uni-ulm.de 132 305 339 269 2092 2600
66 http://www.uab.es 265 383 300 118 2480 3036
78 http://www.rdg.ac.uk 442 398 418 600 3494 3690
87 http://www.uit.no 258 359 569 519 3040 3696
99 http://www.utsa.edu 537 433 306 829 3941 4329
10 10 http://www.mcw.edu 489 351 767 1311 4460 5180
11 12 http://www.fordham.edu 1215 159 924 1256 5246 5510
12 11 http://www.biu.ac.il 627 674 305 612 4867 5843
13 13 http://www.iitb.ac.in 352 1092 403 337 5812 7436
14 15 http://www.gvsu.edu 878 567 848 1741 6613 7441
15 14 http://www.iisc.ernet.in 628 1036 570 229 6199 7659
16 16 http://www.stevens.edu 1351 663 717 1087 7158 7790
17 17 http://www.cwu.edu 892 855 713 1602 7519 7799
18 18 http://www.weber.edu 1060 564 1428 2060 7864 8568
19 19 http://www.nmu.edu 803 958 791 2183 8412 9544
20 20 http://www.uniandes.edu.co 1211 1354 686 322 8846 10526
384 Univ Access Inf Soc (2010) 9:375–386
123
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21 23 http://www.ttuhsc.edu 1627 830 1530 2087 10191 10659
22 21 http://www.iitk.ac.in 1293 1369 683 530 9275 11167
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29 28 http://www.lcsc.edu 1376 1009 1682 3186 11656 14140
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51 46 http://www.njust.edu.cn 2182 2434 2174 3801 20075 25707
52 56 http://www.spc.edu 3338 1779 5678 4707 24177 26409
53 54 http://www.tokai.ac.jp 3075 2177 5189 3335 23382 26446
54 55 http://www.miem.edu.ru 2181 2880 5095 2893 23870 27138
55 53 http://www.jct.ac.il 2687 3103 1833 3335 22954 27318
56 57 http://www.hebau.edu.cn 2308 3002 2437 5445 24506 27786
57 52 http://www.ujn.edu.cn 1581 3298 2646 3531 22531 28311
58 58 http://www.rdc.ab.ca 3062 2822 3417 4163 24992 28988
59 60 http://www.ensicaen.fr 2640 3897 2978 1824 25670 29666
60 59 http://www.aubg.bg 4069 3203 1573 2824 25347 30379
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... The present study which is a short and systematic review is performed in July-August of 2012 aims to assess active websites on Islamic lifestyle based on webometric criteria. In the first step, webometric criteria were detected including visibility, Richfile, Size and Scholar, then these criteria identified in the world countries and compared to each other (13). By using Islamic lifestyle keywords, related sources to this field were chosen from websites which were active in October-November of 2012. ...
... The present study which is a short and systematic review is performed in July-August of 2012 aims to assess active websites on Islamic lifestyle based on webometric criteria. In the first step, webometric criteria were detected including visibility, Richfile, Size and Scholar, then these criteria identified in the world countries and compared to each other (13). By using Islamic lifestyle keywords, related sources to this field were chosen from websites which were active in October-November of 2012. ...
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In 2000, Jakob Nielsen, the world's leading expert on Web usability, published a book that changed how people think about the Web-Designing Web Usability (New Riders). Many applauded. A few jeered. But everyone listened. The best-selling usability guru is back and has revisited his classic guide, joined forces with Web usability consultant Hoa Loranger, and created an updated companion book that covers the essential changes to the Web and usability today. Prioritizing Web Usability is the guide for anyone who wants to take their Web site(s) to next level and make usability a priority! Through the authors' wisdom, experience, and hundreds of real-world user tests and contemporary Web site critiques, you'll learn about site design, user experience and usability testing, navigation and search capabilities, old guidelines and prioritizing usability issues, page design and layout, content design, and more!
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Web sites have been deployed to create and sustain business competitiveness in a trend of emerging Web technologies and growing e-commerce. One critical success factor of e-commerce is the ability to allow information to be retrieved from a Web site in an efficient and effective manner. Such ability, being determined by both the Web site structure and the Web page organization, can be measured in terms of accessibility and popularity of Web pages. The relationship between accessibility and popularity of web pages is dynamic in nature and can be analyzed to enhance a Web design. Having observed the lack of means to measure information retrieval of a Web site, this paper purports to introduce a guideline to evaluate Web page accessibility based on several structural-based accessibility models where an innovative accessibility–popularity (A–P) analysis is deployed to measure and, thereby, to modify a Web structure. Both push (i.e. demand driven) strategies and pull (i.e. design driven) strategies are incorporated into such guideline. Further, accessibility models are analyzed and compared in order to identify appropriate applications for each model. The paper is concluded by a summary of future directions of the accessibility models.
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We present an extensive analysis of long-term statistics of the queries to websites using logs collected on several web caches in Russian academic networks and on US IRCache caches. We check the sensitivity of the statistics to several parameters: (1) duration of data collection, (2) geographical location of the cache server collecting data, and (3) the year of data collection. We propose a two-parameter modification of the Zipf law and interpret the parameters. We find that the rank distribution of websites is stable when approximated by the modified Zipf law. We suggest that website popularity may be a universal property of Internet.