Webometrics

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Webometrics

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History

• Since 2004, the Webometrics ranking is published
  twice a year (January and July).
• This ranking has a coverage of more than 16,000
  higher education institutions.
• The most recent ranking is the January 2009
  Edition.

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Methodology

• The unit for analysis is the institutional
  domain, so only universities and research centers
  with an independent web domain are considered.
• University activity is multi-dimensional. So the
  ranking is built based on combining a group of
  indicators of web presence that measures these
  different aspects.

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Indicators

• Size the number of pages in a domain (as
  recovered by search engines)
• Visibility the number of unique external links
  received by a domain
• Rich File the number of files of certain file
  types in a domain
• Scholar the number of papers and citations in a
  domain

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Metrics

• For each indicator, the universities are ranked.
• Then the ranks of four indicators are combined
  according to a formula as follows.

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Verifiable Data

• The only source for the data of this ranking is a
  small set of globally available, free access
  search engines.
• All the results can be duplicated according to
  the described methodologies, taking into account
  the explosive growth of the web contents, their
  volatility and the irregular behavior of the
  commercial engines.

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Bad Practices

• The use of link farms and paid backlinks to
  improve the position in this rankings is not
  acceptable.
• The involved institutions does not have a place
  in this ranking and will not be classified in
  future editions.
• Random checks are made to ensure the correctness
  of the data obtained.

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Ranking of Interests

1. 55 "National_Taiwan_University" 116 87 46 13
2. 179 "National_Chiao_Tung_University" 90 178 171
   590
3. 273 "National_Taiwan_Normal_University" 211 270
   400 527
4. 274 "National_Cheng_Kung_University" 316 421 235
   53
5. 282 "National_Sun_Yat-Sen_University" 333 405
   348 28
6. 308 "National_Tsing_Hua_University_Taiwan" 161
   502 220 328
7. 370 "National_Central_University" 427 576 355
   30
8. 384 "National_Chung_Cheng_University" 321 446
   390 644
9. 391 "National_Chengchi_University" 336 414 492
   675
10. 491 "Tamkang_University" 461 563 806 550
11. 529 "I-Shou_University" 318 855 397 469
12. 564 "National_Chung_Hsing_University" 448 713
    529 861

We need to work on size, visibility, and rich
files, while keeping our strength in scholar.
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Ranking of Interests

1. 659 "Providence_University" 543 1,067 600 280
2. 716 "Fu_Jen_Catholic_University" 622 848 610
   1,321
3. 748 "Feng_Chia_University" 616 1,191 959 156
4. 772 "Yuan_Ze_University" 409 1,021 574 1,564
5. 836 "NTUST" 1,068 1,325 563 120
6. 851 "Shih_Hsin_University" 617 1,356 948 336
7. 896 "Tunghai_University" 418 1,235 810 1,470
8. 905 "National_Dong_Hwa_U" 816 1,544 580 200
9. 914 "Soochow_University_Taiwan" 560 1,393 1,042
   665
10. 921 "Chaoyang_University_of_T" 885 1,500 803 174
11. 924 "NYUST" 719 1,470 1,212 109

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URL Naming

• Each institution should choose a unique
  institutional domain that can be used by all the
  websites of the institution.
• Avoid changing the institutional domain as it has
  a devastating effect on the visibility values.
• The alternative or mirror domains should be
  disregarded.
• Use of well known acronyms
• Should consider including descriptive word, like
  the name of the city, in the domain name.
• Change IP address to domain name!

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Content Create

• Allow a large proportion of staff, researchers or
  graduate students to be potential authors.
• Individual persons or teams should maintain their
  own websites.
• Libraries, documentation centers and similar
  services can be responsible of large databases,
  including bibliographic ones and large
  repositories (thesis, pre-prints, and reports)
• Hosting external resources can be interesting for
  third parties and increase the visibility
  Conference websites, software repositories,
  scientific societies and their publications,
  especially electronic journals.

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Content Convert

• Important resources available in non-electronic
  format can be converted to web pages easily.
• Most of the universities have a long record of
  activities that can be published in historical
  web sites.
• Other resources, as candidate for conversion,
  include past activities reports or pictures
  collections.

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Interlinking

• Measuring and classifying the links from others
  can be insightful.
• You should expect links from your natural
  partners
• locality or region
• similar organizations
• portals covering your topics
• colleagues or partners personal pages.
• Make an impact in your common language community.
• Check for the orphaned pages, i.e. pages not
  linked from another.
• Most popular pages or directories are relevant.
  

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Language

• The WWW audience is truly global, so one should
  not think locally.
• Language versions, especially in English, are
  mandatory not only for the main pages, but for
  certain selected sections such as scientific
  documents.

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Rich Files

• Although html is the standard format of web
  pages, sometimes it is better to use rich file
  formats.
• Provide versions of different formats.

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Search Engine Issues

• Search engine friendly design
• Avoid cumbersome navigation menus based on Flash,
  Java or JavaScript that can block the robot
  access.
• Deep nested directories or complex interlinking
  can block robots too.
• Databases and even highly dynamic pages can be
  invisible for some search engines, so use
  directories or static pages instead or as an
  option.
• Plain is good.

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Archiving

• Maintain a copy of old or outdated material in
  the site.
• Archive media materials in web repositories.
  Collections of videos, interviews, presentations,
  animated graphs, and even digital pictures could
  be very useful in the long term.

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Standards for Sites

• The use of meaningful titles and descriptive
  meta-tags can increase the visibility of the
  pages.
• Add authoring info, keywords and other data about
  the web sites.

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Challenge

• If the web performance of an institution is below
  the expected position according to their academic
  excellence, university authorities should
  reconsider their web policy, promoting
  substantial increases of the volume and quality
  of their electronic publications.
• Again, NSYSU needs to improve on size,
  visibility, and rich files, while keeping the
  strength in scholar.

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Experiments

• For each institutional domain, we collect the
  data from search engines, per the description of
  methodology.
• Then we compare our ranking against the
  Webometrics ranking.
• We need to verify whether our data agree with
  theirs. It may not agree exactly, but we can
  evaluate the correlation.

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Size

• Number of pages recovered from four engines
• Google, Yahoo, Live Search and Exalead
• For each engine, results are log-normalized to 1
  for the highest value.
• For each domain, maximum and minimum results are
  excluded.
• An institution is assigned a rank according to
  the combined sum.

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Visibility

• The total number of unique external links
  received by a site
• Data gathered from Yahoo, Live and Exalead
  (Google excluded)
• For each engine, results are log-normalized to 1
  for the highest value.
• An institution is assigned a rank according to
  the combined sum.

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Rich Files

• Four different file formats
• Adobe Acrobat (pdf)
• Adobe PostScript (ps)
• Microsoft Word (doc)
• Microsoft Powerpoint (ppt)
• Data (number of files) are extracted using Google
• Merging the results for each file type after
  log-normalization, in the same way as described
  before

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Scholar

• 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.

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Number of Swaps

• For two rankings of domains (institutions), say r
  and s, the number of swaps to bring ranking r to
  s is defined computationally by
• If the top-rank domain in s, say x, ranks 5th in
  r, then 4 swaps is needed for to bring x to top.
• Find the second-rank domain of s in r, bring it
  to second.
• Continue until the entire order is correct.
• Accumulate the number of swaps, say N.
• Smaller N is better.

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Test 1 03/27/2009

• Scholar (n 23) N 17
• Size (n 23) N 28
• Rich files (n 23) N 62
• Scholar (n 100) N 555
• Note the worst-case scenario is n(n-1)/2 swaps,
  and a random ranking is around n(n-1)/4.