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Wikipedia on H-index ---- another excellent article, and also very interesting!

Mike Ciavarella's picture

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This article is about the index of scientific research impact. For the economic measure, see Herfindahl index.

The h-index is an index
that quantifies both the actual scientific productivity and the
apparent scientific impact of a scientist. The index is based on the
set of the scientist's most cited papers and the number of citations
that they have received in other people's publications. The index can
also be applied to the productivity and impact of a group of
scientists, such as a department or university or country. The index
was suggested by Jorge E. Hirsch, a physicist at UCSD, as a tool for determining theoretical physicists' relative quality[1] and is sometimes called the Hirsch index or Hirsch number.

Hirsch suggests that, for physicists, a value for h of about 10-12
might be a useful guideline for tenure decisions at major research
universities. A value of about 18 could mean a full professorship,
15–20 could mean a fellowship in the American Physical Society, and 45 or higher could mean membership in the United States National Academy of Sciences.[2]



[edit] Definition and purpose

The index is based on the distribution of citations received by a given researcher's publications. Hirsch writes:

A scientist has index h if h of his Np papers have at least h citations each, and the other (Np - h) papers have at most h citations each.

H-index from a plot of decreasing citations for numbered papers

H-index from a plot of decreasing citations for numbered papers

In other words, a scholar with an index of h has published h papers each of which has been cited by others at least h times.[3] Thus, the h-index
reflects both the number of publications and the number of citations
per publication. The index is designed to improve upon simpler measures
such as the total number of citations or publications. The index works
properly only for comparing scientists working in the same field;
citation conventions differ widely among different fields.

The h-index serves as an alternative to more traditional journal impact factor
metrics in the evaluation of the impact of the work of a particular
researcher. Because only the most highly cited articles contribute to
the h-index, its determination is a relatively simpler process. Hirsch has demonstrated that h has high predictive value for whether a scientist has won honors like National Academy membership or the Nobel Prize. In physics, a moderately productive scientist should have an h equal to the number of years of service while biomedical scientists tend to have higher values.

[edit] Calculating h

The h-index can be manually determined using free Internet databases, such as Google Scholar. Subscription-based databases such as Scopus and the Web of Knowledge provide automated calculators. Each database is likely to produce a different h
for the same scholar, because of different coverage in each DB: Google
Scholar has more citations than Scopus and Web of Science but each of
their smaller citation collections tends to be more accurate.

The topic has been studied in some detail by Lokman I. Meho and Kiduk Yang.[4] Web of Knowledge
was found to have strong coverage of journal publications, but poor
coverage of high impact conferences (a particular problem for Computer
Science based scholars); Scopus has better coverage of conferences, but poor coverage of publications prior to 1992; Google Scholar has the best coverage of conferences and most journals (though not all), but like Scopus has limited coverage of pre-1990 publications. Google Scholar has also been criticized for including gray literature in its citation counts.[5]
However, the Meho and Yang study showed that the majority of the
additional citation sources Google Scholar uses are legitimate refereed
forums. It has been suggested that in order to deal with the sometimes
wide variation in h for a single
academic measured across the possible citation databases, that one
could assume false negatives in the databases are more problematic than
false positives and take the maximum h measured for an academic.[6]

It should be remembered that the content of all of the databases,
particularly Google Scholar, continually changes, so any research on
the content of the databases risks going out of date.

[edit] Advantages

The h-index was intended to address the main disadvantages of
other bibliometric indicators, such as total number of papers or total
number of citations. Total number of papers does not account for the
quality of scientific publications, while total number of citations can
be disproportionately affected by participation in a single publication
of major influence. The h-index is intended to measure
simultaneously the quality and sustainability of scientific output, as
well as, to some extent, the diversity of scientific research. The h-index
is much less affected by methodological papers proposing successful new
techniques, methods or approximations, which can be extremely highly
cited. For example, one of the most cited condensed matter theorists,
John P. Perdew, has been very successful in devising new approximations
within the widely used density functional theory.
He has published 3 papers cited more than 5000 times and 2 cited more
than 4000 times. Several thousand papers utilizing the density
functional theory are published every year, most of them citing at
least one paper of J.P. Perdew. His total citation index is close to 39
000, while his h-index is large, 51, but not unique. In contrast, the condensed-matter theorist with the highest h-index (94), Marvin L. Cohen, has a lower citation index of 35 000. One can argue that in this case the h-index reflects the broader impact of Cohen's papers in solid-state physics due to his larger number of highly-cited papers.

[edit] Criticism

There are a number of situations in which h may provide misleading information about a scientist's output:[7]

  • The h-index is bounded by the total number of publications.
    This means that scientists with a short career are at an inherent
    disadvantage, regardless of the importance of their discoveries. For
    example, Évariste Galois' h-index is 2, and will remain so forever. Had Albert Einstein died in early 1906, his h-index
    would be stuck at 4 or 5, despite his being widely acknowledged as one
    of the most important physicists, even considering only his
    publications to that date.
  • The h-index does not consider the context of
    citations. For example, citations in a paper are often made simply to
    flesh-out an introduction, otherwise having no other significance to
    the work. h also does not resolve other contextual instances:
    citations made in a negative context and citations made to fraudulent
    or retracted work. (This is true for other metrics using citations, not
    just for the h-index.)
  • The h-index does not account for confounding factors. These
    include the practice of "gratuitous authorship", which is still common
    in some research cultures, the so-called Matthew effect, and the favorable citation bias associated with review articles.
  • The h-index has been found to have slightly less predictive
    accuracy and precision than the simpler measure of mean citations per
    paper.[8] However, this finding was contradicted by another study.[9]
  • While the h-index de-emphasizes singular successful
    publications in favor of sustained productivity, it may do so too
    strongly. Two scientists may have the same h-index, say, h = 30,
    but one has 20 papers that have been cited more than 1000 times and the
    other has none. Clearly scientific output of the former is more
    valuable. Several recipes to correct for that have been proposed, such
    as the g-index, but none has gained universal support.
  • The h-index is affected by limitations in citation data
    bases. Some automated searching processes find citations to papers
    going back many years, while others find only recent papers or
    citations. This issue is less important for those whose publication
    record started after automated indexing began around 1990. Citation
    data bases contain some citations that are not quite correct and
    therefore will not properly match to the correct paper or author.
  • The h-index does not account for the number of authors of a
    paper. If the impact of a paper is the number of citations it receives,
    it might be logical to divide that impact by the number of authors
    involved. (Some authors will have contributed more than others, but in
    the absence of information on contributions, the simplest assumption is
    to divide credit equally.) Not taking into account the number of
    authors could allow gaming the h-index and other similar
    indices: for example, two equally capable researchers could agree to
    share authorship on all their papers, thus increasing each of their h-indices. Even in the absence of such explicit gaming, the h-index and similar indices tend to favor fields with larger groups, e.g. experimental over theoretical.

[edit] Comparison with other metrics

The h-index grows as citations
accumulate and thus it depends on the 'academic age' of a researcher.
Using papers published within a particular time period, e.g within the
last 10 years, would allow to measure the current productivity as
opposed to the lifetime achievement.

Various proposals to modify the h-index in order to emphasize different features have been made.[11][12][13][14]

[edit] See also

[edit] References

  1. ^ Hirsch, J. E. (2005). "An index to quantify an individual's scientific research output". PNAS 102 (46): 16569–16572. doi:10.1073/pnas.0507655102. 
  2. ^ Peterson, Ivars (December 2, 2005). "Rating Researchers", Science News Online. 
  3. ^ "Physicist Proposes New Way to Rank Scientific Output". Retrieved on 2008-07-03.
  4. ^ Meho,
    L. I.; Yang, K. (2007). "Impact of Data Sources on Citation Counts and
    Rankings of LIS Faculty: Web of Science vs. Scopus and Google Scholar".
    Journal of the American Society for Information Science and Technology 58 (13): 2105–2125. doi:10.1002/asi.20677.
  5. ^ Jacsó, Péter (2006). "Dubious hit counts and cuckoo's eggs". Online Information Review 30 (2): 188–193. doi:10.1108/14684520610659201. 
  6. ^ Sanderson, Mark (2008). "Revisiting h measured on UK LIS and IR academics". Journal of the American Society for Information Science and Technology 59 (7): 1184–1190. doi:10.1002/asi.20771. 
  7. ^ Wendl, Michael (2007). "H-index: however ranked, citations need context". Nature 449 (7161): 403. doi:10.1038/449403b. 
  8. ^ Sune Lehmann, Andrew D. Jackson, Benny E. Lautrup (2006). "Measures for measures". Nature 444 (7122): 1003–4. doi:10.1038/4441003a. PMID 17183295. 
  9. ^ Hirsch J. E. (2007). "Does the h-index have predictive power?". PNAS 104: 19193-19198. doi:10.1073/pnas.0707962104. 
  10. ^ Frances Ruane & Richard S. J. Tol (2008). "Rational (successive) h -indices: An application to economics in the Republic of Ireland". Scientometrics 75 (2): 395–405. doi:10.1007/s11192-007-1869-7. 
  11. ^ Sidiropoulos,
    Antonis; Katsaros, Dimitrios; Manolopoulos, Yannis (2007). "Generalized
    Hirsch h-index for disclosing latent facts in citation networks". Scientometrics 72 (2): 253–280. doi:10.1007/s11192-007-1722-z.
  12. ^ g-index
  13. ^ Jayant S Vaidya (December 2005). "V-index: A fairer index to quantify an individual's research output capacity". BMJ 331: 339-c-1340-c. 
  14. ^ Katsaros D., Sidiropoulos A., Manolopous Y., (2007), Age Decaying H-Index for Social Network of Citations in Proceedings of Workshop on Social Aspects of the Web Poznan, Poland, April 27, 2007

[edit] External links

[edit] Publications related to h-index

  • Ball, Philip (2005). "Index aims for fair ranking of scientists". Nature 436 (7053): 900. doi:10.1038/436900a. 
  • Kelly, C. D.; Jennions, M. D. (2006). "The h index and career assessment by numbers". Trends Ecol. Evol. (Amst.) 21 (4): 167–70. doi:10.1016/j.tree.2006.01.005. PMID 16701079. 
  • Lehmann, S.; Jackson, A. D.; Lautrup, B. E. (2006). "Measures for measures". Nature 444 (7122): 1003–4. doi:10.1038/4441003a. PMID 17183295. 
  • Sidiropoulos, Antonis; Katsaros,
    Dimitrios; Manolopoulos, Yannis (2007). "Generalized Hirsch h-index for
    disclosing latent facts in citation networks". Scientometrics 72 (2): 253–280. doi:10.1007/s11192-007-1722-z.
  • Soler, José M. (2007). "A rational indicator of scientific creativity". Journal of Informetrics 1 (2): 123–130. doi:10.1016/j.joi.2006.10.004. 
  • Symonds, M. R.; et al. (2006). "Gender differences in publication output: towards an unbiased metric of research performance". PLoS ONE 1: e127. doi:10.1371/journal.pone.0000127. PMID 17205131. 
  • Taber, Douglass F. (2005). "Quantifying Publication Impact". Science 309 (5744): 2166a. doi:10.1126/science.309.5744.2166a. 

[edit] Computing the h-index

[edit] Lists of h-indices

Retrieved from ""

Categories: Bibliometrics | Academic publishing | Index numbers


i dont know. why ISI thinks all of science is same
topic?. most familiar example be biology, we have too many animals,
cats, dogs, goats, sheeps, snakes, monkeys, mouses, and many others.
think about biologists who work directly on one of them, many of them
may have paid more attention and many of them not, may be related to
geographical characteristics and many other factors. then biologists
who worked on mouses got more citation! (for example). does it mean
they have more invention or intellegence. we first should categorize
science more precisely. if we can. then try to find best researchers. 

Konstantin Volokh's picture

The luckiest of talented researchers may get one really good theoretical idea or experimental finding that will remain in science/engineering for long time. Some guy called genius may have 2-4 such ideas. This is what I call the scientific research impact. The papers presenting such impact may be very highly cited or may not.

By no means has the H-index indicated the scientific impact in the sense considered above. The H-index does indicate, however, personal success, hard work, activity, influence etc. It is probably not a bad idea to use it as an argument in promoting people. In view of the severe industrialization of science H-index is a good indicator. 

You may find my viewpoint somewhat old-fashioned. However, I cannot imagine that when you ask what a guy did in science the answer is that the guy had a very high H-index .

Mike Ciavarella's picture

I agree with you.

But why you expect so much from a integer number.  Einstein 44, Fermi 50, Jim Rice 60? Of course it is too short information, to distinguish between them (Probably Jim Rice doesn't deserve to be higher than Einstein for example....).

So there is an ingredient of age, of "industrialized" production of papers.

However, the total number of paper, used until recently, was even WORSE!   Many people have 500 papers!

A good check is to see the RATIO H/TOTAL number of papers.  In the early stage of career, one has N=H=0, then goes to N=H=1, and so far is NOT very significant.  I suspect H becomes significant for higher than 5 or 10.

For sure my H of 13 is lower than these people, and as far as this is true, I suspect it is a good index.   If my H were higher than Einstein, the next day I will say it is bullshit!

I have noticed the majority of people against H are those who have it low....

Whereas the people who are always in politics, check the head of NIH peer review, have quite low.  There isn't much you can do to have huge H unless you work very hard.

Are there H indexes for Dalai Lama or Al Gore? Not, but they won Nobel prize.

Is Nobel prize always a sign of equal capabilities?  Probably not either.

people who think very positive about H-Factor thinks all papers who cite a special paper want to give a possitive credit to it, and they think it as some sort of gathering public opinion. but it is not! there are many other factors else "thinking it is best" which leads to improve a citation of a paper.

dont forget 90% of papers has not cited. low quality works are too much, [this is our main reason to use this factors]. many people dont review well. and just depend on those things that they find at first and they have heard about them, they dont select a work.

1. one important case is when people who have no any
idea about advantages and disadvantages of different methods, they build their
work on most popular one!. 

2. if some one is in kazakestan, he prefer to use a work has done in kasakestan, may be because of its availability not superiority. he has to use it. he has not select it. 

3. sometimes something is detail of a work, i use anything to do it, most biogists use FEM  to model a bone. they dont use MESHLESS even if it be better in that case. their focus is on the bone not on the method. they did not select it. or when for example i want to provide a reference to a fact which is stated in many papers. i use any one not the best one.

4. many people just cited a work to show their works have applications. for example i saw a paper well cited who used a technology to do something, people who cited that paper was not used that technology, they were from developers of the technology and found an application for their papers.  may be this method be very unefficient in my eyes as a user.









 Mike, you have very positive attitude about scientific society and i respect this positive attitude. but in fact many authors are refer to any thing they find, i have seen it when i was in third world more!. c i am sure it is also in other countries who people research to survey not to compete. this is why we use such factors to filter, but wein this way we filter low-qualities based on what low quaility says!


Mike Ciavarella's picture

I hope you don't mind these comments: 

As far as I understand you are in Singapore and that is a good place to do research.  Many more people are less lucky than you.

I would improve, if I were you, my clarity in English - frankly often I don't follow or understand your messages.  I do not know your paper, but maybe your MAIN problem is just this, and not citation?

The way you write is CRUCIAL in science, almost like in fiction.  Read some Grisham and you will see why writing about anything, he is so popular. 

You should consider taking some energies to actually write papers, more than talking about it !   You seem to write more or less the same things all the time in imechanica.  Why?  You need to pose focused questions, not 200 times the same questions, if people do not answer maybe the question is not clear, or is not popular, or people give up to read all this?

So relax, enjoy life!

If you have a confused plan like Eric said lately, then also relax. 

Thanks for your valuable recommendations. I try to improve my English.i read very much but i do not write so much. i must imporve my writing. I thought my statements are understandable.

Singapore is really good, labs are very equipped, and people are very nice.even my personal topic is very popular and I like it.

My posts about citation system was part of my research about evaluation of scientific systems and personally i found citation system very problematic although it is very popular. it is a bitter fact. i think there was no incorrect fact in my reasons.

I dont work on mehcnaics now, my posts are related to scientometrics and wiki-style systems, and web 2.0.

if you did not like to answer I should not address you. sorry.

Best regards.

roozbeh sanaei.

Mike Ciavarella's picture


Your research is of marginal interest for imechanica!

Most people here are in mechanics.

You should find I am sure, blogs in your area. There must be more in web2.0

Do you want me to look for you? 

in biochemistry/bioengineering OpenWetWare is good but it has not a discussion room.if you know anything like imechanica in bioengineering or biochemistry it is great!. i would be very thankful if you lead me to a discussion room (other than NATURE discussion room) about scientometrics.

Mike Ciavarella's picture

Before the blog, do you know well the literature and the journals on the subject?


See eg. what they just did in UK:

Research Excellence Framework

HEFCE is working to develop new arrangements for the assessment and
funding of research. The new arrangements - the Research Excellence
Framework (REF) - will be introduced after the 2008 Research Assessment
Exercise (RAE).

Outcomes of the REF consultation

We recently consulted on proposals for the REF (HEFCE 2007/34). The consultation closed on 14 February 2008 and an analysis of responses to the consultation is now available.

In the light of the feedback received we will continue to develop
the REF, with two significant modifications to the proposals. These
were agreed following discussion with the Department for Innovation,
Universities and Skills (DIUS). The modifications are that:

  • the timetable for designing the new framework will be extended by 12 months to allow sufficient time for development
  • there will no longer be such a clear distinction between the
    arrangements for science-based subjects and those for all other
    subjects; for all subjects the assessment will include some combination
    of metrics-based indicators, including bibliometrics where appropriate,
    as well as input from expert panels.

Further details of these modifications are available:

The REF will consist of a single unified framework for the funding
and assessment of research across all subjects. It will make greater
use of quantitative indicators in the assessment of research quality
than the present system, while taking account of key differences
between the different disciplines. Assessment will combine quantitative
indicators - including bibliometric indicators wherever these are
appropriate - and light-touch expert review. Which of these elements
are employed, and the balance between them, will vary as appropriate to
each subject.

The REF will be developed as a single unified framework throughout
2008 and 2009. Aspects of the framework will be phased in from 2011-12,
and it will fully drive research funding for all disciplines from 2014.

Next steps

We will now proceed to pilot the new bibliometric indicator and
undertake other activities to develop the REF. Details of our plans for
this work can be found in Circular letter 13/2008 to heads of HEFCE-funded higher education institutions.


The Government announced in March 2006
its intention to replace the Research Assessment Exercise (RAE) after
2008 with an assessment system based on metrics. A working group, whose
members included representatives of the four UK higher education
funding bodies and a number of government departments, then developed a
consultation ('Reform of higher education research assessment and funding').

The Chief Executives of the Arts and Humanities Research Council and HEFCE established an expert group
to advise on the use of research metrics in the arts and humanities in
particular. The group's final report was published in October 2006.

Following the consultation, the Government announced in the 2006 pre-Budget Report the development of a revised scheme for assessment of quality and allocation of funding. The Department for Education and Skills outlined details of the scheme in a press release. A letter from the Secretary of State gave further guidance to HEFCE.

The Government also announced that the 2008 RAE will be conducted as planned, using the criteria already published by the subject panels.

We set out our initial plans for the development of the new system in 'Future framework for research assessment and funding' (HEFCE Circular letter 06/2007).

In November 2007 we published proposals for consultation (HEFCE 2007/34). These were informed by two research and evaluation reports on the use of bibliometric techniques:

Further information

To receive news and updates on the REF, please join our REF-NEWS mailing list.

Queries about the REF should be sent to


Mike Ciavarella's picture

Researchers may play dirty to beat REF

7 February 2008

By Zoë Corbyn

Senior academics predict a boom in manipulation of citations under new system. Zoe Corbyn reports.

kinds of manipulation and gamesmanship that researchers could employ to
boost their research ratings under the system set to replace the
research assessment exercise have been outlined in frank detail to Times Higher Education by a number of senior academics.

the forthcoming Research Excellence Framework, which is out for
consultation until 14 February, research quality in the sciences will
be judged largely on the basis of the number of times an academic's
work is cited by his or her peers.

One potential technique to
maximise citations could harm young researchers looking to climb the
citation ladder. Senior scientists could manipulate publication
procedures used by their research groups to prevent first and
second-year PhD students being added as secondary authors to group
publications, a practice seen as affording students an early career
boost. They could later be used as lead authors on group work on the
understanding that they cited earlier papers from the group where their
names did not appear. The practice would circumvent the Higher
Education Funding Council for England's plan to exclude "self
citations" - where academics cite their own earlier work - and would
allow senior researchers to improve their citation counts substantially.

system that undermines the aspirations and ambitions of our very best
early-career researchers would be a step backwards," said one pro

Another senior academic said universities might
introduce institutional publication policies to ensure researchers
achieved maximum citations. "If Hefce chooses to harvest all papers
produced from an institution, the cat is really among the pigeons,"
said the source. "Institutions will have to start policing every paper
that leaves the institution destined for publication."

But behaviour that could hinder young researchers is just the tip of the iceberg, according to others.

clubs" - cartels of colleagues who do deals to cite each others' work -
may become increasingly common. Observers also predict a boom in the
number of spurious or sensational papers that are more likely to grab
attention and citations.

"Lots of people quote bad science," one pessimistic senior researcher said.

"Citation clubs are already operating in the US," said one head of department.

lot of academic work is already based on mutual admiration and back
scratching, and that will intensify," said another anonymous source.

Concerns that game-playing within the REF will undermine collaborative and interdisciplinary research are also being expressed.

is much better to ensure that joint papers aren't published so that the
chances for citation by a group working in the same area are
increased," said one professor.

Concerns are particularly acute
within the engineering community, which Hefce acknowledges is not well
covered by the Web of Science database that it intends to use to count

"The one thing you can absolutely guarantee is that
people will skew behaviour in order to make the best out of whatever
metrics are in place," said Sue Ion, the vice-president of the Royal
Academy of Engineering. She has been working on the society's
submission to the REF consultation.

"If citations become the
be-all and end-all - and Hefce has never said they will - then academic
groups will look at where they should be publishing. The worry is that
rather than doing collaborations with small to medium enterprises and
industry that may not result in any publications, they will try to do
detailed work to report in top-flight journals."

Dr Ion added
that the society was looking at other metrics measures that might be
introduced to measure interdisciplinary and collaborative research but
that "light-touch peer review had a fair bit of attraction". However,
she said, there was no "one-size-fits-all" solution for all of
engineering's branches.

Among the more colourful suggestions
offered by researchers as to how to improve citation counts under the
REF is the use of more colons in the titles of papers.

Times Higher Education
was referred by one academic to a paper by an American academic, Jim
Dillon, "The emergence of the colon: an empirical correlate of
scholarship", in the journal American Psychologist in 1981.
It records a high correlation between the use of colons in the titles
of published academic papers and other quality indicators, including
citation counts.

"We might follow this to include at least two
colons in the titles of our papers so as to ensure the highest
recognition," said the academic, adding that the downside might be a
mass breakout of what Dr Dillon might call "colonic inflation".

"I understand that it is extremely painful," he said.



Hefce says: "The main incentive for researchers
will be to publish work that is recognised as high quality by peers and
becomes highly cited by the international academic community.
Short-term game-playing is far less likely to achieve this than
responsible strategies to nurture the talent ... and for publishing
work that enhances the group's international reputation." But more
mischievous academics have suggested some ways to maximise one's rating:

- Do not cite anyone else's research, however relevant it is, as it boosts others' citation counts and increases their funding;

Do not publish anything in journals with low citation rates, a group
that includes lots of applications-based journals, as it will lower
your citations;

- Do not do scientific research in fields not yet well covered by Thomson Scientific database, as your output won't be visible;

- Do not report negative results: they are unlikely to get cited;

- Join a citation club.

Readers' comments

  • Charles Jannuzi
    7 February, 2008

    You have a horrible situation in the sciences where people have
    their names on papers they haven't even read, let alone contributed
    anything to. Authorship should remain authorship. So when you see an
    article with one person's name followed by AND and another person's
    name, co-authorship has some sort of meaning. I have had my names on
    papers as co-author and actually written more for the paper than the
    first name (we flipped a coin, or we went by alphabetical order, or we
    took turns). And yet when evaluations roll around, articles that I have
    written as much as 80% of the content for have counted less because
    co-authorship somehow means less or nothing. The reason is all this
    indiscriminate inclusion of names of NON-AUTHORS. It's horrendously

  • Onlooker
    7 February, 2008

    Try this strategy to increase your citations. Publish very critical
    articles about the work of eminent US academics. They will rush into
    print to repudiate your work, thereby increasing your citation count.
    Repeat with other well-known non-UK academics.

  • K. V. Pandya
    8 February, 2008

    Having a high number of citations is absolutely the wrong way to go
    about measuring research. How can the number of citations measure the
    importance of the research, how applicable is the research? Already
    there are researchers citing and rewarding thier friends. I have
    noticed this at the conferences where one speaker praises the
    conference chair and the conference chair praises the speaker, within a
    space of half an hour. It goes on openly, needless to say it will go on
    behind closed doors. The citation clubs are an example. This form of
    research assessment will be open to wider abuse than it currently is.
    Already we have seen people talking ways of improving citations:
    joining citation clubs, using colon (like used here), not putting
    research students names on it, etc.

    Getting more and quality publications should be the way
    forward. This should be based on how does the research contribute to
    knowledge of the peers, students, industry and wider community? This
    should be important, not how many friends, research collaborators,
    former colleagues, yes and foes cite one's publications. In addition to
    this how about having HEFC sponsored conferences on different fields of

    HEFC needs to look more at how the research is disseminated
    not who has read the publication. Though this could be useful, it
    should not be the only way. It should only play a minor role in the
    research assessment.

  • Barry G Blundell
    8 February, 2008

    In a Letter published in 'Nature' in 1948, Denis Gabor elucidated
    the principles of holography, however it was not until the invention of
    the laser in the early 1960's that Gabor's pioneering work came into
    its own. In short, for approximately fifteen years Gabor's Letter
    received scant attention. Today his publication is recognised as a
    seminal work and is cited widely.

    In fact, history shows that pioneering breakthroughs in
    science, technology etc, are seldom immediately recognised. Clearly
    therefore anybody who is interested in playing the RAE game should
    avoid leading the way, but rather jump onto a research bandwagon after
    it has met with establishment approval. An alternative approach is
    again demonstrated in history. Almost universally the invention of the
    transistor is attributed to the work done in the 1940's by Bardeen,
    Brattan and Shockley (1947). Since that time their work has been widely
    recognised and it would be likely that a measure of their citation
    index would be off the scale. Of course, this fails to take into
    account the fact that the transistor was actually invented in the
    1920's. In short, once citations have reached a critical number the
    truth becomes irrelevant.

    Looking back over the last two hundred years or so, it is clear
    that scientists and engineers within the UK have the credit for paving
    the way and despite the vast funding poured into US institutions,
    Britain has managed to play a pivotal role in human advancement. How
    sad therefore to see scientists and engineers in the UK being forced
    down a distorted route which is intended to mimic 'excellence'
    associated with US institutions. Have we learnt so little that we
    really believe that the human creative spirit can be quantified?
    Research is a way of life - a quest for understanding - and is
    something to disseminate to one's peers and students. Unfortunately in
    many UK institutions, students have become third-class customers as the
    RAE game has pushed their importance to one side. The pioneers who pave
    the way are unafraid to enter a darkened room without necessarily
    knowing what they will find and without being unduly concerned as to
    how long their quest will take. The continued RAE exercise simply
    serves to ensure that darkened rooms are avoided and at all times one
    plays safe.

    Although above I have acknowledged the UK's tremendous history
    in science, engineering, and other fields, there have been good times
    and not so good times. I firmly believe that future generations will
    look back on this current period as one of the more dismal times for
    creativity and innovation - simply a very poor copy of the flawed US
    model. Dr Barry G Blundell

  • Aaron Ahuvia
    12 February, 2008

    Clearly, citation rates are a very flawed system for assessing
    research quality. But we need some system for doing this. For every
    problem with citation rates, there are far more serious problems with
    the current non-system system.For example, many universities ask a
    department to rate journals in a discipline. The resulting lists
    generally combine some true insight with a heaping dose of self
    interest on the part of the people making the lists, all mixed up with
    petty prejudices about how "our" (i.e. journals edited by my friends,
    or in my sub-sub-sub area) are better than "their" journals.
    Furthermore, quality is assessed based largely on the journal where
    something is published, rather than on the characteristics of the paper
    itself. When evaluating any new system, we need to keep in mind just
    how lousy the current system is.

    What is really needed is a system of multiple indicators for
    the underlying construct -- in this case research quality -- we are
    trying to measure. Any single measure can always be gamed. Even
    multiple measures can be gamed to a certain extent, but it gets harder
    to fool the system with each additional indicator used. Eventually, it
    just gets easier to do good work than to spend your time figuring out
    how to cheat.

Mike Ciavarella's picture

Research Assessment Exercise
From Wikipedia, the free encyclopedia

Jump to: navigation, search

The Research Assessment Exercise (RAE) is an exercise undertaken approximately every 5 years on behalf of the four UK higher education funding councils (HEFCE, SHEFC, HEFCW, DELNI)
to evaluate the quality of research undertaken by British higher
education institutions. RAE submissions from each subject area, (or unit of assessment)
are given a rank by a subject specialist peer review panel. The
rankings are used to inform the allocation of quality weighted research
funding (QR) each higher education institution receives from their
national funding council.

Previous RAEs took place in 1986, 1989, 1992, 1996 and 2001. The next is scheduled in 2008.



[edit] Scale

In 2001 and 1996 the following descriptions were used for each of the ratings. The scale used in 1992 is given in brackets.

  • 5* (5*) Research quality that equates to attainable levels of
    international excellence in more than half of the research activity
    submitted and attainable levels of national excellence in the
  • 5 (5) Research quality that equates to attainable levels of
    international excellence in up to half of the research activity
    submitted and to attainable levels of national excellence in virtually
    all of the remainder. (Same definition)
  • 4 (4) Research quality that equates to attainable levels of
    national excellence in virtually all of the research activity
    submitted, showing some evidence of international excellence. (Same
  • 3a (3) Research quality that equates to attainable levels of
    national excellence in over two-thirds of the research activity
    submitted, possibly showing evidence of international excellence.
    (Research quality that equates to attainable levels of national
    excellence in a majority of the sub-areas of activity, or to
    international level in some)
  • 3b (3) Research quality that equates to attainable levels of
    national excellence in more than half of the research activity
    submitted. (Research quality that equates to attainable levels of
    national excellence in a majority of the sub-areas of activity, or to
    international level in some)
  • 2 (2) Research quality that equates to attainable levels of
    national excellence in up to half of the research activity submitted.
    (Same definition)
  • 1 (1) Research quality that equates to attainable levels of
    national excellence in none, or virtually none, of the research
    activity submitted. (Same definition)

These ratings have been applied to "units of assessment", such as
French or Chemistry, which often broadly equate to university
departments. Various unofficial league tables have been created of
university research capability by aggregating the results from units of
assessment.[citation needed] Compiling league tables of universities based on the RAE is problematic, as volume and quality are both significant factors.

The 2008 RAE will use a four-point quality scale, and will return a
profile, rather than a single aggregate quality score, for each unit.
The quality levels—based on assessment of research outputs, research
environment and indicators of esteem—are defined as:

Quality that is world-leading in terms of originality, significance and rigour
Quality that is internationally excellent in terms of originality,
significance and rigour but which nonetheless falls short of the
highest standards of excellence
Quality that is recognised internationally in terms of originality, significance and rigour
Quality that is recognised nationally in terms of originality, significance and rigour
Quality that falls below the standard of nationally recognised
work. Or work which does not meet the published definition of research
for the purposes of this assessment.

Each unit of assessment will be given a quality profile - a
five-column histogram - indicating the proportion of the research that
meets each of four quality levels or is unclassified.

[edit] Assessment process

The assessment process for the RAE focuses on quality of research
outputs (which usually means papers published in academic journals and
conference proceedings), research environment, and indicators of
esteem. Each subject panel determines precise rules within general
guidance. For RAE 2008, institutions are invited to submit four
research outputs, published between January 2001 and December 2007, for
each full-time member of staff selected for inclusion.[1]

In response to criticism of earlier assessments, and developments in
employment law, the 2008 RAE does more to take into account part-time
workers or those new to a sufficient level of seniority to be included
in the process.

[edit] Criticism

The RAE has not been without its critics, since 1996 the AUT, now incorporated within the UCU, has maintained a policy of opposition to the Research Assessment Exercise.[2] In its view,

The RAE has had a disastrous impact on the UK higher education
system, leading to the closure of departments with strong research
profiles and healthy student recruitment. It has been responsible for
job losses, discriminatory practices, widespread demoralisation of
staff, the narrowing of research opportunities through the
over-concentration of funding and the undermining of the relationship
between teaching and research.

The official Review of Research Assessment, the 2003 "Roberts Report" commissioned by the UK funding bodies,[3] recommended changes to research assessment, partly in response to such criticisms.

The House of Commons Science and Technology Select Committee considered the Roberts report, and took a more optimistic view,[4] asserting that, "the
RAE had had positive effects: it had stimulated universities into
managing their research and had ensured that funds were targeted at
areas of research excellence",
it concluded that "there had been a marked improvement in universities' research performance". Nevertheless, it argued that "the RAE in its present form had had its day", and proposed a reformed RAE, largely based on Roberts' recommendations.

[edit] Planned changes to RAE system

It was announced [1] in the 2006 Budget that after the 2008 exercise a system of metrics
would be developed in order to inform future allocations of QR funding.
Following initial consultation with the higher education sector, it is
thought that the Higher Education Funding Councils will introduce a
metrics based system of assessment for Science, Technology Engineering
and Medicine subjects. A process of peer review is likely to remain for
mathematics, statistics, arts, humanities and social studies subjects.

[edit] References

  1. ^ RAE 2008 Definitions
  2. ^ RAE 2008 University and College Union
  3. ^ Review of research assessment - report by Sir Gareth Roberts to the UK funding bodies, May 2003
  4. ^ Science and Technology Committee, Eleventh Report, 15 September 2004

[edit] External links

Retrieved from ""

Categories: Research | Public bodies and task forces of the United Kingdom government



The key to getting cited is
being found.
- totally obvious truism





There is no substitute for
getting published in one of “the journals” everyone in your discipline reads.
Here are a couple hints:

  • In your article, have you cited multiple articles from a specific journal?
    Is so, that’s a good candidate.
  • You can check ISI’s Journal Citation Reports to find journal impact factors.
  • Sometimes, getting published in a high quality niche journal may be
    preferable. Don’t rule them out.


Don’t be shy about asking the
marketing representative of your press if they intend to send review copies to
your favorite journals. Be sure that you get covered in Choice. This is
the main book review journal that is used by academic libraries.


Information overload is our
problem these days. Most researchers use finding aids like article databases and
library catalogs to locate information. Your work needs to jump out as relevant
and significant during a rapid scroll through hundreds of citations. The
Title is the Key!!!


This is not the place to
demonstrate your artistic/expressive nature. Titles should be informative.
People need to know what your article or book is about based on the title alone.
If you are working within a particular theoretical tradition, you can use some
jargon or names, but make sure it will still make sense to a novice. The most
important terms for describing your work should be in the title. Every word
should serve a purpose. Some advice is, hand only your title to colleagues and
see if they can figure out what your article or book is about.


To maximize your chances of
being found, you have to understand how article databases work. Keyword
searching looks at the following fields: title, subject headings,
author-supplied subject headings, and the abstract. Very few use relevancy
ranking. Most use Boolean logic. For those that do use relevancy ranking, the
title is given stronger weight, so the most important “search terms” should be
in the title.


The abstract gives you the
greatest opportunity to design a strategy that will get your article found.

Here is a sample strategy:

  1. Write an informative abstract that tries to reduce the article to a
    paragraph. Try to make the abstract a substitute for reading the article.
    Summarize your conclusions, mention your methodology, mention any theoretical
    framework you are using, name the population studied on both the local and
    larger levels.
  2. Think broadly and imagine every research area that your study would ideally
    influence and generate a list of relevant terms that these other researchers
    might use in a search. Revise your abstract, trying to insert these thoughts and
  3. After you have a draft that is a good reduction and will draw in researchers
    that are outside of your primary field, look over your abstract for any repeated
    words. Look for synonyms, including some field specific terms or jargon, if
    appropriate. Use broader and narrower terms. Each word is taking up prime real
    estate. Make it work for you.


Library catalogs are the main finding aid for books.
The main topic fields that are searched in a library catalog are: title, series
title, table of contents, and sometimes summaries from the book jacket.

Go ahead and write an abstract for the book and submit
it to the publisher. Maybe it will get used for the book jacket.

For each chapter title, think of it as a separate
entity and follow the suggestions for the title of the whole work. You want each
chapter to be capable of being found on its own.

Go back and look at the titles and the chapter titles.
If words are repeated, look for synonyms.

Mike Ciavarella's picture

Maybe RoozbehSanaei or some other imechanica user wants to use any of these 5 sofwares using Google Scholar to improve them and perhaps link them to Excel files so that we can do large statistics, perhaps by countries, or by institution, or by area of study, like mechanics?


or invent your own !!


Mike Ciavarella's picture


function [h ncited]=hindex(name,varargin)
%HINDEX  Computes the h-index of an author from Google Scholar.
%   HINDEX(AUTHORNAME) computes the h-index of the author AUTHORNAME, on
%   the basis of the publications referenced by Google Scholar
%   ( An active internet connection is required.
%   The index h is defined as "the number of papers with citation number
%   higher or equal to h", and has been proposed by J.E. Hirsch to
%   "characterize the scientific output of a researcher" [Proc. Nat. Acad.
%   Sci. 46, 16569 (2005)]. Note that the number of citations referenced by
%   Google Scholar may be lower than the actual one (old publications are
%   not available online).
%   The string AUTHORNAME should contain the last name, or the initial(s)
%   of the first name(s) followed by the last name, of the author (eg,
%   'A. Einstein'). Do not put the initial(s) after the last name. The scan
%   is not case sensitive. Points (.) and spaces ( ) are not taken into
%   account. See Google Scholar Help for more details about the syntax.
%   Example: HINDEX('A. Einstein') returns 43 (ie: 43 papers by A. Einstein
%   have been cited at least 43 times, according to Google Scholar).
%   H = HINDEX(AUTHORNAME) only returns the h-index, without display.
%   HINDEX(AUTHORNAME, 'Property1',...) specifies the properties:
%     'verb'       also displays the list of papers returned by Google
%                  Scholar, rejecting the ones for which AUTHORNAME is not
%                  one of the authors.
%     'plot'       also plots the 'Cited by' number as a function of the
%                  paper rank.
%   HINDEX should be used with care. Many biases exist (homonyms, errors
%   from Google Scholar, old papers are not available online, but
%   unpublished or draft papers are...) For the true h-index of an author,
%   it is recommended to use an official citation index database (eg, ISI).
%   Use HINDEX just for fun.
%   Remark: Massive usage of hindex may be considered by the Google
%   Scholar server as a spam attack, and may invalidate the IP number of
%   your computer. If this happens, you get an 'Internet connection failed'
%   error message -- but you still can use Google Scholar from a web
%   browser.
%   F. Moisy,
%   Revision: 1.11,  Date: 10-jul-2006

% History:
% 22-jan-2006: v1.00-1.10, first versions.
% 07-jul-2006: v1.11, check ML version; help text improved; use properties

% check the matlab version:
if str2double(version('-release'))<14,
    error('hindex requires Matlab 7 (R14) or higher.');


% clean the input text:
name=strrep(name,'.',' ');
name=strrep(name,'  ',' ');

ncit=0;   % total number of citation
ncitinthispage=0; % number of citation in the current page

while seenextpage,
    % find the web page:
    pagename=['' num2str(100*(numpage-1)) '&q=%22author%3A' strrep(name,' ','+author%3A') '%22'];
    if nargout==0,
        disp(['Scanning: ' pagename]);
    [s, res]=urlread(pagename);
    if ~res,
        error('Internet connection failed.');       

    rem=s; % remainder of the string

    while strfind(rem,'Cited by '),
        pauth1 = strfind(rem,'<font color=green>')+18; pauth1=pauth1(1);
        pauth2 = strfind(rem(pauth1:min(end,(pauth1+500))),'</font>')-1; pauth2=pauth2(1);
        authstring = lower(rem(pauth1:(pauth1+pauth2-1))); % list of authors of the paper
        authstring = strrep(authstring,'<b>','');
        authstring = strrep(authstring,'</b>','');
        authstring = strrep(authstring,'&hellip;','...');

        % check that the required name is indeed in the author list.
        if length(pos),
            if pos>1,
                % check for wrong initials (eg, 'ga einstein' should not
                % match for 'a einstein')
                if ((pl>='a')&&(pl<='z'))||(pl=='-'),
            if pos<(length(authstring)-length(name)),
                % check for wrong 'suffix' (eg, 'einstein-joliot' should not
                % match for 'einstein')
                if ((nl>='a')&&(nl<='z'))||(nl=='-'),

        if paperok, % if the required name is indeed in the author list
            ncit = ncit+1;
            ncitinthispage = ncitinthispage +1;
            p=strfind(rem,'Cited by ')+9; p=p(1);
            pend=strfind(substr,'<'); pend=pend(1);
            if any(strncmpi(varargin,'verb',1))
                disp(['#' num2str(ncit) ': (' num2str(ncited(ncit)) '), ' authstring]);
            if any(strncmpi(varargin,'verb',1))
                disp(['rejected: ' authstring]);
            p=strfind(rem,'Cited by ')+9; p=p(1);
    if any(strncmpi(varargin,'verb',1))
        disp(' ');
    if ncit==0,
        if ((ncited(ncit)<2)||(~length(findstr(rem,'<span class=b>Next</span>')))),
end; % while seenextpage

if length(ncited),
    % sort the list (it should be sorted, but sometimes GS produces unsorted results)
    ncited=sort(ncited); ncited=ncited(ncit:-1:1);

    % computes the H-factor:

    % plot the 'Cited by' number:
    if any(strncmpi(varargin,'plot',1))
        xlabel('Paper rank'); ylabel('Number of citations');
        title(['h-index plot for ''' name ''' (h=' num2str(h) ')']);

    % some displays if no output argument:
    if nargout==0,
        disp(['Number of cited papers: ' num2str(length(ncited))]);
        disp(['''Cited by'' list: ' num2str(ncited)]);
        disp(['Total number of citations: ' num2str(sum(ncited))]);
        disp(['h-index = ' num2str(h)]);
        clear h;
    if nargout==0,
        disp('No result found');
        clear h;

data mining in citation data is very beneficial, we can use the strategies they used already in market research to find out  need of scientific society.does some one else work on market research for scientific products?. in  my eyes use of markey research for scientific planning could be a good work. i have found research work on proteomic based drug discovery is growing with a very high rate from mining this data with this methods. but i am going to develop a more general software in this regard. any way thanks for your websites. i am reading the web page scripts now.


Market Research in Wikipedia


Mike Ciavarella's picture

I get an error which seems from the matlab web site that had appeared previously, but maybe it is worse?  google scholar maybe interprets any call from matlab as an attack even for a single use!

If I go to

it works

but if I write

there is the error

whereas if I write plain


it works again.

How to solve this?

Regards, Mike

Google has provided several APIs (Application Programming Interfaces) for outsiders to use Google's data.

There's a Google project called citations-gadget which may be what you're looking for.  You can find other APIs at

My own views on h-index have been summed up in an excellent blog post by Bee (of BackReaction) called

We have only ourselves to judge on each other.  

To quote Bee

"Don't fall for shortcuts. Under time pressure, people tend to look for easy criteria to judge on other people or their projects. Such might be the citation index, the number of papers, prominent coauthors or grants obtained. In all instances scientists should judge on other's work by themselves. This requires that scientists have enough time for this judgement. Time is essential, but too short in today's research atmosphere. For a thought on how to cut back on researcher's duties, see previous post on Research and Teaching."

-- Biswajit

This link is very useful at least for me. Time shortage forces people to use numbers.research evaluation enhances like any other methodologies. Dynamic review paper also is a way to judge about different works in a cooperative manner.

Mike Ciavarella's picture

Scientometric is a journal full of this type of discussions. You should check it.

Only looking at one issue, e.g.

Subscribed Journal Scientometrics

Volume: 76, Issue: 1

July 2008

Link to Publisher's Homepage


Down Arrow 

Save Selected |
Clear All

The evaluation of university departments and their scientists: Some
general considerations with reference to exemplary bibliometric
publication and citation analyses for a Department of psychology

Krampen, Günter
pp. 3 - 21

Bibliographic Page
| Article Full Text PDF (389 KB)

Scientometric definition of science: In what respect is the humanities
more scientific than mathematical and social sciences?

Eto, Hajime
pp. 23 - 42

Bibliographic Page
| Article Full Text PDF (240 KB)

Relation of seminal nanotechnology document production to total nanotechnology document production — South Korea

Kostoff, Ronald N.; Barth, Ryan B.; Lau, Clifford G. Y.
pp. 43 - 67

Bibliographic Page
| Article Full Text PDF (970 KB)

Great expectations: The role of Open Access in improving countries’ recognition

Sotudeh, Hajar; Horri, Abbas
pp. 69 - 93

Bibliographic Page
| Article Full Text PDF (304 KB)

Ranking Taiwanese management journals: A case study

Kao, Chiang; Lin, Hsiou-Wei; Chung, San-Lin; Tsai, Wei-Chi; Chiou, Jyh-Shen; Chen, Yen-Liang; et. al.
pp. 95 - 115

Bibliographic Page
| Article Full Text PDF (258 KB)

The mathematical relation between the impact factor and the uncitedness factor

Egghe, Leo
pp. 117 - 123

Bibliographic Page
| Article Full Text PDF (153 KB)

How do we measure the use of scientific journals? A note on research methodologies

Moghaddam, Golnessa Galyani; Moballeghi, Mostafa
pp. 125 - 133

Bibliographic Page
| Article Full Text PDF (156 KB)

PageRank for bibliographic networks

Fiala, Dalibor; Rousselot, François; Ježek, Karel
pp. 135 - 158

Bibliographic Page
| Article Full Text PDF (601 KB)

The delineation of nanoscience and nanotechnology in terms of journals and patents: A most recent update

Leydesdorff, Loet
pp. 159 - 167

Bibliographic Page
| Article Full Text PDF (434 KB)

What makes an article influential? Predicting impact in social and personality psychology

Haslam, Nick; Ban, Lauren; Kaufmann, Leah; Loughnan, Stephen; Peters, Kim; Whelan, Jennifer; et. al.
pp. 169 - 185

Bibliographic Page
| Article Full Text PDF (217 KB)

The influence of self-citation corrections on Egghe’s g index

Schreiber, Michael
pp. 187 - 200

Bibliographic Page
| Article Full Text PDF (309 KB)


that is a nice journal, i think it discusses an important issue despite it's low IF!. I also read Nature comments in this regard. most of papers are based in this assumption : "Authors choose their references!" but in fact " authors just use any hing that they can use it faster and justifies their work better. i think this picture from PHD comics is near to reality and also funny. even best scientists do like this for those papers which are not very related to their main topic. It does not mean scientists are doing weak works, It means bibliometrics are not very trustful.

if you are interested in this topic IMU report on citation statistics is also very informative.


Mike Ciavarella's picture

In fact, h-index usually is used for authors, but now they are also using for countries or journals, see

You seem here to introduce a new ideas --- to have h-index for subjects, and also to perhaps monitor the increase of h-index.  It is certainly interesting.  You should give a try.  Any other imechanician interested to help us?



I think h factor for subjects is even more rational than h factor for authors.

personally i prefer to compare citation number of a paper with citation number of refered papers for evaluating a paper in a subject. i think it is very rational.




Mike Ciavarella's picture

michele ciavarella

I am trying with Java Script.

[I like JScript because it's free, works in all versions of Windows, linux, Mc and even handphone!]

 Please make me aware if you got more result with matlab.

Mike Ciavarella's picture


 About QuadSearch


The metasearch
engines are web services designed to transfer the user's queries to
multiple existing search engines. A metasearch engine does not maintain
its own index of documents. It collects and reorganizes the result
lists (top-k lists), then it returns the processed data to the user.

Compared to a classic single search engine, a metasearch engine offers:

  • Increased web coverage
  • Improved retrieval effectiveness
  • Effortless invocation of multiple search engines

QuadSearch is a brand new and constantly evolving metasearch engine. It is hosted by the Raptor web server, which belongs to the Data Engineering Laboratory (DELAB), of Aristotle University of Thessaloniki.

It has been created by Leonidas Akritidis, George Voutsakelis, Dimitrios Katsaros and Panayiotis Bozanis.

main purpose is to build a powerful scientific tool, that will be used
by the academic community in order to retrieve useful information.
Their secondary objective focuses on finding better and faster ranking

QuadSearch's heart is
the KE Algorithm, which is the mechanism that determines the
classification of the collected results. KE Algorithm was invented by
the founders of this engine and has also been the basis for Search Engine Analyzer.
Apart from KE Algorithm, QuadSearch is capable of using a variety of
several other ranking algorithms, to classify the results.

As mentioned
above, QuadSearch is constantly under construction. If you have any
suggestions for it, or you want to report a security issue, please let
us know, by filling the appropriate contact form.


Mike Ciavarella's picture


I start to think the best sofware is this from collegues in Paris --- maybe I can contact them!

In fact, I suspect you can use authomatic scripts by using for example the string

or maybe multiple authors so we can play with.  The problem with Google Scholar is that it seems it is NOT classified by LOCATION or INSTITUTION, but only AUTHOR and FIELD.

However, see the help:


  • Use the OR operator with quotes for names with non-unique spellings; for example,
    The guy you think to know as Fred Vernier should be writen:

    "Frédéric Vernier" OR "Frederic Vernier"

  • On the other hand you still miss some of his articles. If you type
    "F Vernier" you will have all his articles but ... also articles from someone else. You then have to deselect
    them is order to find the right h-curve !
  • Warning Restricting an author to a given domain will remove all the articles
    google scholar couldn't classify ! For instance articles not written in english. Restricting to given years
    will also remove all articles google scholar couldn't determine the year.
  • Most of the time data must be cleaned ! remove articles from others and
    merge articles (when typos made google duplicate a single article)
  • We disclaim everything, especially every problem resulting from the data returned by Google Scholar.
  • Data you enter is not logged yet ... but we want to save all
    the cleaning work done by users in order to improve the data source !
  • You may save the url in the address textfield of your browser but we
    will change the format soon and the old address will return an error.
  • You may enter many names in the author textfield to evaluate a full team of researsher but the system is already slow ...
  • You may experience denial of service from google scholar
    sometime. Retry 2 or 3 times. If you still have nothing come back the
    day after.
  • I did compute the h-view of the whole UIST conference and the first 3 for the 20th anniversary of UIST. The poster was presented at UIST'07.


Mike Ciavarella's picture


  • The number of articles is 0
  • The total number of citations is 624
  • The maximum number of citations is 56
  • The h-number (or h-index) is 13
  • The m-number (or m-index) is 0.34210526315789475 (1970-2008)
  • but then the output is very slow....both in web1 or web2 format. not sure why!


    Mike Ciavarella's picture


    Dear M. Ciavarella

    This should work for a list of people:

    name={'a einstein','f moisy','c bruni'};
    for n=1:length(name),
        disp([name{n} ' ' num2str(h(n))]);

    F. Moisy

    Mike Ciavarella's picture

    Citation metrics

    Publish or Perish User's Manual

    Citation metrics

    Publish or Perish calculates the following citation metrics:

    • Total number of papers
    • Total number of citations
    • Average number of citations per paper
    • Average number of citations per author
    • Average number of papers per author
    • Hirsch's h-index and related parameters, shown as
      h-index and Hirsch a=y.yy, m=z.zz in the output
    • Egghe's g-index, shown as g-index in the output
    • The contemporary h-index, shown as hc-index
      and ac=y.yy in the output
    • Two variations of the individual h-index, shown as
      hI-index and hI,norm in the output
    • The age-weighted citation rate
    • An analysis of the number of authors per paper.

    Please note that these metrics are only as good as their input. We recommend
    that you consult the following topics for information about the limitations of
    the citation metrics and the underlying sources that Publish or Perish uses:


    The h-index was proposed by J.E. Hirsch in his paper An index to quantify
    an individual's scientific research output
    , arXiv:physics/0508025 v5 29 Sep 2005. It is defined as

    A scientist has index h if h of his/her Np papers have at least h
    citations each, and the other (Np-h) papers have no more than h
    citations each.

    It aims to measure the cumulative impact of a researcher's output by looking
    at the amount of citation his/her work has received. Publish or Perish
    calculates and displays the h index proper, its associated
    proportionality constant a (from Nc,tot =
    ), and the rate parameter m (from h ~ mn, where
    n is the number of years since the first publication).

    The properties of the h-index have been analyzed in various papers; see for
    example Leo Egghe and Ronald Rousseau: An informetric model for the
    , Scientometrics, Vol. 69, No. 1 (2006), pp. 121-129.

    Info This metric is shown as h-index and Hirsch a=y.yy,
    in the output.


    The g-index was proposed by Leo Egghe in his paper Theory and practice of
    the g-index
    , Scientometrics, Vol. 69, No 1 (2006), pp. 131-152. It is
    defined as follows:

    [Given a set of articles] ranked in decreasing order of the number of
    citations that they received, the g-index is the (unique) largest number such
    that the top g articles received (together) at least g2

    It aims to improve on the h-index by giving more weight to highly-cited

    Info This metric is shown as g-index in the output.

    Contemporary h-index

    The Contemporary h-index was proposed by Antonis Sidiropoulos, Dimitrios
    Katsaros, and Yannis Manolopoulos in their paper Generalized h-index for
    disclosing latent facts in citation networks
    , arXiv:cs.DL/0607066
    v1 13 Jul 2006

    It adds an age-related weighting to each cited article, giving (by default;
    this depends on the parametrization) less weight to older articles. The
    weighting is parametrized; the Publish or Perish implementation uses
    gamma=4 and delta=1, like the authors did for their experiments.
    This means that for an article published during the current year, its citations
    account four times. For an article published 4 years ago, its citations account
    only one time. For an article published 6 years ago, its citations account 4/6
    times, and so on.

    Info This metric is shown as hc-index and ac=y.yy in
    the output.

    Individual h-index (2 variations)

    The Individual h-index was proposed by Pablo D. Batista, Monica G. Campiteli,
    Osame Kinouchi, and Alexandre S. Martinez in their paper Is it possible to
    compare researchers with different scientific interests?
    Scientometrics, Vol 68, No. 1 (2006), pp. 179-189.

    It divides the standard h-index by the average number of authors in the
    articles that contribute to the h-index, in order to reduce the effects of
    co-authorship; the resulting index is called hI.

    Publish or Perish also implements an alternative individual h-index,
    hI,norm, that takes a different approach: instead of dividing the
    total h-index, it first normalizes the number of citations for each paper by
    dividing the number of citations by the number of authors for that paper, then
    calculates hI,norm as the h-index of the normalized citation
    counts. This approach is much more fine-grained than Batista et al.'s; we
    believe that it more accurately accounts for any co-authorship effects that
    might be present and that it is a better approximation of the per-author impact,
    which is what the original h-index set out to provide.

    Info These metrics are shown as hI-index (Batista et al.'s) and
    hI,norm (PoP's) in the output.

    Age-weighted citation rate (AWCR, AWCRpA) and AW-index

    The age-weighted citation rate was inspired by Bihui Jin's note The
    AR-index: complementing the h-index
    , ISSI Newsletter, 2007, 3(1), p.

    The AWCR measures the number of citations to an entire body of work, adjusted
    for the age of each individual paper. It is an age-weighted citation rate, where
    the number of citations to a given paper is divided by the age of that paper.
    Jin defines the AR-index as the square root of the sum of all age-weighted
    citation counts over all papers that contribute to the h-index. However, in the
    Publish or Perish implementation we sum over all papers instead, because we feel
    that this represents the impact of the total body of work more accurately. (In
    particular, it allows younger and as yet less cited papers to contribute to the
    AWCR, even though they may not yet contribute to the h-index.)

    The AW-index is defined as the square root of the AWCR to allow comparison
    with the h-index; it approximates the h-index if the (average) citation rate
    remains more or less constant over the years.

    The per-author age-weighted citation rate is similar to the plain AWCR, but
    is normalized to the number of authors for each paper.

    Info These metrics are shown as AWCR, AWCRpA and
    AW-index in the output.

    Publish or Perish User's Manual - Topic last modified on 27/01/08 12:19
    Copyright © 1990-2008 Tarma Software
    Research. All rights reserved.

    Is there any scientometric way to calculate a contribution of each ref. on a paper? it may be important.

    Mike Ciavarella's picture


    I just did IJSS 

    Most cited papers and H-factor of some mechanics journals -- IJSS

    who wants to do JMPS, and the other journals?



    Subscribe to Comments for "Wikipedia on H-index ---- another excellent article, and also very interesting!"

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