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The World Wide Web has changed research habits, and these changes were further expanded when “Web 2.0” became popular in 2005. Bibliometrics is a helpful tool used for describing patterns of publication, for interpreting progression over time, and the geographical distribution of research in a given field. Few studies employing bibliometrics, however, have been carried out on the correlative nature of scientific literature and Web 2.0.
The aim of this bibliometric analysis was to provide an overview of Web 2.0 implications in the biomedical literature. The objectives were to assess the growth rate of literature, key journals, authors, and country contributions, and to evaluate whether the various Web 2.0 applications were expressed within this biomedical literature, and if so, how.
A specific query with keywords chosen to be representative of Web 2.0 applications was built for the PubMed database. Articles related to Web 2.0 were downloaded in Extensible Markup Language (XML) and were processed through developed hypertext preprocessor (PHP) scripts, then imported to Microsoft Excel 2010 for data processing.
A total of 1347 articles were included in this study. The number of articles related to Web 2.0 has been increasing from 2002 to 2012 (average annual growth rate was 106.3% with a maximum of 333% in 2005). The United States was by far the predominant country for authors, with 514 articles (54.0%; 514/952). The second and third most productive countries were the United Kingdom and Australia, with 87 (9.1%; 87/952) and 44 articles (4.6%; 44/952), respectively. Distribution of number of articles per author showed that the core population of researchers working on Web 2.0 in the medical field could be estimated at approximately 75. In total, 614 journals were identified during this analysis. Using Bradford’s law, 27 core journals were identified, among which three (Studies in Health Technology and Informatics, Journal of Medical Internet Research, and Nucleic Acids Research) produced more than 35 articles related to Web 2.0 over the period studied. A total of 274 words in the field of Web 2.0 were found after manual sorting of the 15,878 words appearing in title and abstract fields for articles. Word frequency analysis reveals “blog” as the most recurrent, followed by “wiki”, “Web 2.0”, ”social media”, “Facebook”, “social networks”, “blogger”, “cloud computing”, “Twitter”, and “blogging”. All categories of Web 2.0 applications were found, indicating the successful integration of Web 2.0 into the biomedical field.
This study shows that the biomedical community is engaged in the use of Web 2.0 and confirms its high level of interest in these tools. Therefore, changes in the ways researchers use information seem to be far from over.
Over the past two decades, the World Wide Web has changed researchers’ habits. These changes were further expanded when “Web 2.0” became popular in 2005 [
Bibliometrics is a helpful and widely used tool for describing patterns of publication and interpreting temporal evolutions and the geographical distribution of research in a given field. However, few studies employing bibliometrics have been carried out on the correlative nature of scientific literature and Web 2.0. A bibliometric analysis was performed in 2009 by Chu and Xu [
The aim of the present study was to provide an overview of Web 2.0 implications in the biomedical literature and to answer the following questions: What is the growth rate of biomedical literature on Web 2.0?; What are the key publications, countries, and authors in the field?; Which Web 2.0 terms are the most recurrent in biomedical literature?; and, Are the various applications of Web 2.0 expressed in the biomedical literature? Established bibliometric methods have been used to perform the present study. One example is the identification of core journals using Bradford’s law of scattering which has, to the best of our knowledge, never been done to study literature related to Web 2.0.
The search for papers to be included in this study was carried out on February 7, 2013, using the PubMed database [
The final search strategy was the following: (“social networking”[MeSH Terms] AND (web [Title/Abstract] OR internet [Title/Abstract])) OR (“web 2.0” [Title/abstract] OR “Medicine 2.0” [Title/abstract] OR “Health 2.0” [Title/abstract] OR “Biology 2.0” [Title/abstract] OR “science 2.0” [Title/abstract] OR Social Media [MH] OR Syndication [Title/Abstract] OR wiki [Title/Abstract] OR Blogging [MeSH Terms] OR blog* [Title/Abstract] OR microblogg* [Title/Abstract] OR Cloud computing [Title/Abstract] OR folksonom* [Title/Abstract] OR social bookmark* [Title/Abstract]) AND (1951:2012 [DP]) AND (journal article [PT]), where MeSH stands for “Medical Subject Headings”, DP “Date of Publication”, and PT “Publication Type”.
Data downloaded from PubMed in Extensible Markup Language (XML) were processed through developed hypertext preprocessor language (PHP) scripts, then were imported to Microsoft Excel 2010. All articles were manually reviewed by the author of this article and those not related to Web 2.0 were eliminated. When no abstract was available for a reference, PubMed “Related citations” were consulted to determine the eligibility of the article in the present study.
Microsoft Excel served for assessing the growth of literature, for journals, language of publication, authorship pattern, and number of publications per country. The average yearly growth rate was calculated as the mean percentage of annual growth for the period studied, with average yearly growth rate=(Current year total - Previous year total)/Previous year total [
Average yearly growth rate and percentage of articles published in English were also calculated for the whole PubMed database for the period 2002-2012. This period was chosen because it corresponds to the period where articles related to Web 2.0 were found in this study.
Bradford’s law of scattering has been used extensively in the information science literature to describe the dispersion of articles in any scientific field [
The Journal Citation Reports (Thomson Reuters) was used for Impact Factor determination. For the determination of affiliation of authors, England, Scotland, Northern Ireland, and Wales were clustered into the United Kingdom. Words from both title and abstract fields were recovered for keyword frequency calculation using TextSTAT 2.9 software [
The publication search turned in a total of 1578 references. After manual sorting and elimination of inappropriate references, 1347 articles were retained for inclusion in the study.
As shown in
Growth of literature (annual number and cumulative number).
A total of 614 journals were identified during this analysis. As shown in
Bradford zones of scattering for Web 2.0 literature.
Zones | Number of journals | Percentage of journals | Number of articles | Cumulative number of articles (%) | Description | Ratio (number of journals) | Theoretical ratio (1:n:n2) | Theoretical number of journals |
Core journals | 27 | 4.4% | 428 | 428 (31.7) | Producing <53 and ≥7 articles | 1 | 1 | 27 |
Middle | 178 | 29.0% | 510 | 938 (61.7) | Producing ≤6 and ≥2 articles | n=6.6 | n=6.6 | 178 |
Last | 409 | 66.6% | 409 | 1347 (100) | Producing 1 article | n2=15.1 | n2=43.4 | 1172 |
Total | 614 | 100.0% | 1347 | 1377 |
Distribution of number of articles per journal (solid line) and cumulated percentage of articles (dotted line).
Major Web 2.0 publishing journals (journals publishing more than six articles).
Journal | Articles, |
Impact factor | MeSH termsb | |||
Studies in Health Technology and Informaticsa | 53 (3.93) | N/A | Biomedical Technology; Medical Informatics | |||
Journal of Medical Internet Researcha | 36 (2.67) | 3.768 | Information Services; Internet; Medical Informatics; Research | |||
Nucleic Acids Researcha | 35 (2.60) | 8.278 | Nucleic Acids | |||
Cyberpsychology, Behavior and Social Networkinga | 33 (2.45) | N/A | Behavior; Computer Communication Networks/utilization; Multimedia/utilization; Psychology, Social; User-Computer Interface | |||
AMIA. Annual Symposium proceedings / AMIA Symposium. AMIA Symposiuma | 24 (1.78) | N/A | Medical Informatics Applications; Medical Informatics Computing | |||
BMC Bioinformaticsa | 21 (1.56) | 3.024 | Computational Biology | |||
Medical Reference Services Quarterlya | 21 (1.56) | N/A | Information Services; Information Systems; Libraries, Medical; Library Services | |||
Medical Teachera | 20 (1.48) | 1.824 | Education, Medical | |||
Nurse Educatora | 19 (1.41) | 0.562 | Education, Nursing | |||
PLoS Onea | 17 (1.26) | 3.73 | Medicine; Science | |||
Bioinformatics (Oxford, England)a | 16 (1.19) | 5.323 | Computational Biology; Genome | |||
Health Information and Libraries Journala | 11 (0.82) | N/A | Libraries, Medical; Medical Informatics | |||
Genome Biologya | 10 (0.74) | 10.288 | Biology; Genetics; Genome | |||
Journal of Medical Systemsa | 10 (0.74) | 1.783 | Computers; Delivery of Health Care; Information Systems | |||
BMJ (Clinical research ed.)a | 9 (0.67) | 17.215 | Medicine | |||
Journal of Digital Imaginga | 9 (0.67) | 1.1 | Computer Systems ; Radiographic Image Enhancement; Radiology Information Systems | |||
Journal of Health Communicationa | 9 (0.67) | N/A | Communication; Health Education; Health Promotion; Health Services; Health | |||
Cyberpsychology & Behavior: the impact of the Internet, multimedia and virtual reality on behavior and societya | 8 (0.59) | N/A | Behavior; Computer Communication Networks/utilization; Multimedia/utilization; Psychology, Social; User-Computer Interface | |||
Health Communicationa | 8 (0.59) | N/A | Communication; Health | |||
Naturea | 8 (0.59) | 38.597 | Science | |||
The Journal of Medical Practice Management : MPMa | 8 (0.59) | N/A | Practice Management, Medical | |||
Vaccinea | 8 (0.59) | 3.492 | Vaccines | |||
American Journal of Pharmaceutical Educationa | 7 (0.52) | N/A | Education; Pharmacy | |||
Annual International Conference of the IEEE Engineering in Medicine and Biology Societya | 7 (0.52) | N/A | Biomedical Engineering | |||
Journal of Dental Educationa | 7 (0.52) | 0.989 | Education, Dental | |||
Journal of the Medical Library Association : JMLAa | 7 (0.52) | N/A | Information Services; Libraries, Medical; Library Science | |||
Medical Educationa | 7 (0.52) | 3.546 | Education, Medical | |||
Caring: National Association for Home Care magazine | 6 (0.45) | N/A | Health Services for the Aged; Home Care Services; Long-Term Care | |||
Database: the journal of biological databases and curation | 6 (0.45) | 4.2 | Computational Biology | |||
Journal of the American Medical Informatics Association : JAMIA | 6 (0.45) | 3.571 | Medical Informatics Applications; Medical Informatics | |||
Nursing education perspectives | 6 (0.45) | N/A | Education, Nursing; Nursing | |||
PLoS computational biology | 6 (0.45) | 4.867 | Computational Biology | |||
Science (New York, N.Y.) | 6 (0.45) | 31.027 | Science | |||
The Journal of Adolescent Health: Official Publication of the Society for Adolescent Medicine | 6 (0.45) | 2.966 | Adolescent Medicine | |||
The Journal of Nursing Education | 6 (0.45) | 1.133 | Education, Nursing | |||
Tobacco Control | 6 (0.45) | 4.111 | Smoking/prevention & control; Tobacco Use; Disorder/prevention & control; Tobacco |
aCore journals according to Bradford’s law of scattering.
bMeSH terms used in the catalog of the National Library of Medicine to describe the journal.
A total of 1355 declared languages were retrieved among the 1347 articles. This disparity could be explained by the fact that some articles have two languages declared in the language field in PubMed. The most commonly used language was English (1301/1355; 96.01%), followed by French (17/1355; 1.25%); Spanish (12/1355; 0.89%); German (8/1355; 0.59%); Italian (4/1355; 0.30%); Dutch (3/1355; 0.22%); Japanese, Portuguese (2/1355; 0.15%); and Danish, Greek, Hungarian, Norwegian, Polish, and Swedish (1/1355; 0.07%). The percentage of publications in English for the whole PubMed database was 90.84% for this given period (2002-2011).
For 395 of the 1347 articles (29.32%), it was impossible to identify the contributing country because the author claimed no affiliation and the articles failed to name the country of publication. Therefore, only 952 of the articles studied could be linked to countries.
The United States was by far the predominant country for authors, with 514 articles (514/952; 54.0%). The second most productive country was the United Kingdom with 87 articles (87/952; 9.1%). Authors from Europe produced 264 articles (264/952; 27.7 %).
Number and percentage of articles published per country relative to the affiliation of authors (n=952).
Country | Articles, |
United States | 514 (54.0) |
United Kingdom | 87 (9.1) |
Australia | 44 (4.6) |
Canada | 41 (4.3) |
China | 40 (4.2) |
Germany | 34 (3.6) |
Spain | 26 (2.7) |
Netherlands | 21 (2.2) |
France | 14 (1.5) |
Italy | 14 (1.5) |
Greece | 11 (1.2) |
Japan | 11 (1.2) |
New Zealand | 10 (1.1) |
Switzerland | 10 (1.1) |
India | 9 (0.9) |
Israel | 9 (0.9) |
Norway | 8 (0.8) |
Sweden | 8 (0.8) |
Portugal | 6 (0.6) |
Belgium | 4 (0.4) |
Ireland | 4 (0.4) |
Austria | 3 (0.3) |
Brazil | 3 (0.3) |
Bulgaria | 3 (0.3) |
Egypt | 3 (0.3) |
Romania | 3 (0.3) |
Turkey | 3 (0.3) |
Luxembourg | 2 (0.2) |
South Africa | 2 (0.2) |
Argentina | 1 (0.1) |
Czech Republic | 1 (0.1) |
Poland | 1 (0.1) |
Singapore | 1 (0.1) |
Slovakia | 1 (0.1) |
In total, 4209 authors were found for the 1347 articles retained, corresponding to 3762 different authors. The great majority of authors (91.54%; 3444/3762) wrote only one article, 6.51% (245/3762) wrote two articles, whereas 73 (1.94%; 73/3762) wrote three or more. The maximum number of articles written by one author was 14.
A total of 274 words in the field of Web 2.0 were found after manual sorting of the 15,878 words belonging to title and abstract fields. Similar words differing by singular/plural, upper/lower case were aggregated and 99 words finally obtained. As shown in
In the general category, “Web 2.0” was the most common expression followed by e-health, Health 2.0, and Medicine 2.0. “Blog” was the predominant category of any Web 2.0 application encountered in the biomedical literature, followed by social networks and wiki (1279, 1199, and 803 occurrences, respectively). Micro-blogging, cloud computing, social bookmarking/document sharing, and syndication were much less represented with 332, 260, 183, and 175 occurrences, respectively.
Word frequency for general, blog, social network, and wiki categories.
General |
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Blog | Social network | Wiki | |||
Word | n | Word | n | Word | n | Word | n |
Web 2.0 | 542 | Blog | 800 | social media | 472 | Wiki | 536 |
e-health | 71 | Blogger | 259 | 336 | Wikipedia | 108 | |
Health 2.0 | 39 | Blogging | 181 | Social network | 327 | Crowdsourcing | 21 |
Medicine 2.0 | 36 | Blogosphere | 30 | MySpace | 29 | MediaWiki | 18 |
Science 2.0 | 8 | Nonbloggers, Blogroll | 2 | Second life | 21 | SubtiWiki | 17 |
e-Research | 3 | Medbloggers, blogspot, Bloglines, blogorrhea, blogsearch | 1 | 9 | WikiPathways | 10 | |
O’Reilly | 2 |
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PatientsLikeMe | 5 | myExperiment | 9 |
eScience | 1 |
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ArrayWiki | 8 |
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EcoliWiki, SNPedia | 7 |
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Pathowiki, PDBWiki | 6 |
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Channelpedia, UMMedWiki | 5 |
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WikiGenes, WikiPharma, Bowiki, TWiki, Proteopedia, | 4 |
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Casepedia, SEQwiki, Gene_Wiki, WikiBuild | 3 |
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WikiProteins, OperonWiki, meta-wiki, OpenToxipedia, CHDWiki, Wikisource, Wikibooks, WikiOpener, RAASWiki | 2 |
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Genewikiplus, WikiMedia, wikispaces, Clinfowiki, wikiprofessional, OpenWetWare, gowiki, sbwWiki, WikiTrust, Wikipedians, Medi-wiki | 1 |
Total | 702 | Total | 1279 | Total | 1199 | Total | 803 |
Word frequency for microblogging, cloud computing, social bookmarking/document sharing, and syndication categories.
Micro blogging | Cloud computing | Social Bookmarking/ |
Syndication | ||||
Word | n | Word | n | Word | n | Word | n |
205 | cloud computing | 209 | YouTube | 89 | podcast | 69 | |
Tweet | 73 | Amazon | 33 | Tag | 31 | RSS | 56 |
micro-blogging | 31 | CloudLCA | 6 | social bookmarking | 29 | syndication | 37 |
12 | CloudMan | 3 | Tagging | 13 | podcasting | 11 | |
Tweeting | 6 | SurveyMonkey, Netvibes, CloudBioLinux, GeoCommons | 2 | Folksonomy | 11 | uBioRSS | 2 |
iScience | 3 | CloudBurst | 1 | video-sharing | 4 |
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micro-blog | 2 |
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Delicious | 3 |
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Digg, CiteULike, Slideshare | 1 |
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Total | 332 | Total | 260 | Total | 183 | Total | 175 |
The appearance of literature relating to Web 2.0 in the biomedical field is recent, and correlates with the year 2005, when Web 2.0 became popular [
Using Bradford’s law of scattering, the theoretical ratio of number of journals (43.4) and theoretical number of journals in the last third (1172) were higher than the values obtained experimentally (15.1 and 409, respectively). Thus, articles related to Web 2.0 are published in a lesser number of journals (n=614) than the expected Bradford theoretical value (n=1377). This can be explained by the innovative nature of the subject studied, which has not yet been taken into account by a great number of journals.
In the list of the 38 journals that published more than six articles, including core journals according to Bradford’s law (
English was by far the most predominant language of the articles included in the study, and the percentage of articles in English was higher compared to the entire PubMed database (96.01% and 90.84%, respectively). This can be explained by the fact that English is the official language for scientific publications in most countries. As mentioned elsewhere [
The United States was by far the most productive country. Europe came second globally, whereas Africa and South America were very poorly represented.
Distribution of number of articles per author shows that the great majority of authors (91.54%; 3444/3762) wrote only one article, whereas 73 (1.94%; 73/3762) wrote three or more. Thus, the core population of researchers working on Web 2.0 in the biomedical field can be estimated to approximately 75.
Considering generalist terms or expressions, the word frequency analysis reveals “Web 2.0” as the most common term, followed by “e-health”, “Health 2.0”, and “Medicine 2.0”, which are the expressions most commonly used to describe Web 2.0 technologies applied in this field [
The most represented category of the eight was blog (1279 occurrences). This can be explained by the fact that blogs are among the oldest Web 2.0 applications and the facility of their implementation has established their popularity. Quite logically, in the second category, “social network”, the well-known Facebook was by far the most represented. Among wikis, Wikipedia was the most represented term. The high number of terms in this category is due to the many applications based on wiki platforms developed by researchers, and most of the articles related to these terms are actually presentations of these applications. The most cited micro-blogging application was, as expected, Twitter, confirming its high popularity. Cloud computing applications, currently on the rise, are also well represented, even though access to them is fairly recent compared to that of blogs or wikis. Amazon, best known for its online shopping website, is cited because it also offers solutions for the development of cloud computing applications. The category social bookmarking / document sharing was predominantly represented by YouTube. Unexpectedly, social bookmarking sites specially developed for the scientific field were scarce (eg, Citeulike), or simply not present (eg, Connotea or Bibsonomy). The same can be said of other categories in which the most represented terms were related to popular applications (Facebook, YouTube, Wikipedia, and Twitter, respectively the first, third, sixth, and tenth most consulted sites in the world according to [
One should be aware that this study presents some limits: for even if PubMed is widely used for bibliometric analysis, it does not contain all biomedical journals [
This paper presents an exploration of the geographical distribution and temporal trends of the biomedical literature related to Web 2.0 found in PubMed, together with an analysis of related words and expressions. The study indicates the ongoing expansion of a field currently dominated by the United States. All categories of Web 2.0 applications abound within the literature, indicating that Web 2.0 has been integrated into the biomedical field. Of note, applications developed specifically for biology and medicine were less represented than their generalist counterparts (eg, Facebook, Twitter). The study of articles published clearly shows a great diversity of journals, including those with significant scientific influence, displaying interest in Web 2.0, and confirms the high level of interest the topic holds for the biomedical community. Therefore, the changes in the informational uses of researchers, initiated by the arrival of the World Wide Web and continued by Web 2.0, seem to be far from over.
impact factor
medical subject headings
hypertext preprocessor language
Extensible Markup Language
The author wishes to thank Graham Waller and Valerie Fong for reviewing this article.
None declared.