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IJBM

eISSN 1724-6008 ORIGINAL RESEARCH ARTICLE

months to years) for an article to be cited because it first must be read and cited by other researchers whose articles require additional time to be published. Furthermore, young researchers are generally disadvantaged since they have by definition published fewer articles than senior researchers and citations build up over time (3). The rapid growth of the World Wide Web has made these limits even more evident. The development of tools that are more Web 2.0 oriented has profoundly changed the scientific communication pro-cess (4). In this context, many Web tools are often referred to as “social media” given their role in supporting communica-tion and building communities (Facebook, Twitter, etc.) (5). Altmetrics is the creation and study of new metrics based on the Social Web for analyzing and informing scholarship (6), thus combining the traditional bibliometrics tools with the use of the Web (7).

All research centers in Italy (defined as IRCCS) by April each year communicate to a central database (http://ricerca. cbim.it/index_en.html) the complete list of scientific publica-tions in their research areas for the Italian Ministry of Health (MoH). The list of published work is one of the main factors for allocating resources to current research activities by the MoH. The judgment is based on the IF, which is also used to DOI: 10.5301/jbm.5000217

Novel bibliometric scores for evaluating research

quality and output: a correlation study with established

indexes

Valeria Scotti1,3, Annalisa De Silvestri2,3, Luigia Scudeller2,3, Paola Abele1, Funda Topuz1, Moreno Curti1

1 Center for Scientific Documentation, Fondazione IRCCS Policlinico San Matteo, Pavia - Italy 2 Service of Biometry & Statistics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia - Italy 3 ALMT-ALL Metrics Team, Fondazione IRCCS Policlinico San Matteo, Pavia - Italy

Introduction

The problem of measuring the scientific and social impact of research publications has been of extreme interest to sci-entists and scholars since the inception of modern science, but open questions still remain on the efficacy of the cur-rent indexes. The journal impact factor (IF) and the h-index are the most well-known indicators based on citation analy-sis (1, 2). These indexes show several limitations; a crucial one is their lack of timeliness. It takes a long time (several

AbSTRACT

Introduction: Novel bibliometric indexes (commonly known as altmetrics) are gaining interest within the scien-tific community and might represent an important alternative measure of research quality and output.

Aims: We evaluate how these new metrics correlate with established bibliometric indexes such as the impact fac-tor (IF), currently used as a measure of scientific production as well as a criterion for scientific research funding, and how they might be helpful in assessing the impact of research.

Methods: We calculated altmetrics scores for all the articles published at our institution during a single year and examined the correlation between altmetrics scores and IFs as a measure of research quality and impact in all departments.

Results: For all articles from the various departments published in a single year, the altmetrics score and the sum of all IFs showed a strong and significant correlation (Spearman’s rho 0.88). The correlation was significant also when the major components of altmetrics, including Facebook, Twitter and Mendeley, were analyzed. The implementation of altmetrics has been found to be easy and effective at both the researcher and librarian levels. Conclusions: The novel bibliographic index altmetrics is consistent and reliable and can complement or be con-sidered a valid alternative to standard bibliometric indexes to benchmark output and quality of research for academic and funding purposes.

Keywords: Altmetrics, Bibliometrics, Hospital, Impact factor, Oncology department

Received: April 15, 2016 Accepted: May 23, 2016 Published online: June 8, 2016 Corresponding author:

Valeria Scotti

Center for Scientific Documentation Fondazione IRCCS Policlinico San Matteo Viale Golgi, 19

27100 Pavia, Italy [email protected]

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allocate funds received from the MoH to departments within each institution.

In this study we wanted to assess the validity of the new metrics as an index of the research impact. For this purpose we examined the correlation between IFs and altmetrics scores obtained in each department of our hospital, taking the Oncology Department as the reference. Our aim was to ascertain whether the altmetrics score could be used as a complementary or alternative index to evaluate the impact of research.

Materials and methods

Samples and tools

We analyzed all full-text articles published in 2013 in in-dexed journals (with a 2012 IF score) by researchers affiliated to our hospital. The list of articles was exactly the same as the one supplied to MoH for funding purposes. Data were collected searching PubMed and Web of Science, and researchers were asked to verify if all the articles they had authored had been retrieved. For each retrieved article, the altmetrics score on Alt-metric.com was searched using the PMID of the article. The 646 papers published in 2013 were then grouped across depart-ments and both the IFs and altmetrics scores were summed up. For all these articles, we listed the altmetrics score as for-mulated by Jason Priem in 2010 (8). Altmetrics tools capture information through the use of metrics from HTML views and downloads of articles, blog posts, tweets, bookmarks, etc. Such information is provided in real time and altmetrics show not only the impact of scientific research by researchers but also the impact of the research on the public through social media (9).

Altmetric.com, PlumX, ImpactStory and PLoS Impact Ex-plorer are currently the main tools that aggregate and provide article-level metrics (10, 11). In particular, the Altmetric.com badges function allows publishers to add altmetrics data with 2 simple lines of code added to the article HTML. Altmetric badges is currently used by leading publishers including Wiley,

Sage, Springer, Nature, Wichtig and many others, which have integrated it into their Web pages. For the purpose of our study we selected Altmetric.com as a major tool aggregating data at the article level.

Statistical analysis

Quantitative variables are described as median and inter-quartile range (IQR), i.e., the 25th and 75th percentiles. The association between IF and the altmetrics score or its com-ponents is expressed through the nonparametric Spearman rho correlation coefficient. Furthermore, we correlated the number of citations in the Web of Science and the number of Mendeley readers or PubMed citations using the non-parametric Spearman rho coefficient. All analyses were per-formed with Stata 13 (StataCorp LP) and a p value below 0.05 was considered statistically significant (12).

Results

A total of 268 of the 646 papers (41.6%) presented an metrics score and 45 out of 53 departments obtained an alt-metrics score (median 14, IQR 3-68). Among the components of the altmetrics score, Mendeley readers was the highest (2,403 citations obtained by 45 departments; median 36, IQR 7-50) followed by Tweeters for a total of 1,998 tweets obtained by 45 departments (median 15, IQR: 6-48) and Facebook walls for a total of 247 obtained by 32 departments (median 5, IQR: 2-9). Less frequent were news outlets, for a total of 74 ob-tained by 13 departments (median 4, IQR: 2-8); bloggers for a total of 70 obtained by 18 departments (median 3, IQR: 1-5); CiteULike readers for a total of 53 obtained by 17 departments (median 2, IQR 1-2); Google authors for a total of 23 obtained by 9 departments (median 2, IQR: 2-3); and F1000 reviews for a total of 18 obtained by 13 departments (median 1, IQR 1-2). The results are summarized in Figure 1.

The median IF by department was 44 (IQR 14-128) and the correlation between the sum of altmetrics scores and the

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sum of IFs relative to all articles published in 2013 calculated for each of the departments of our institution was very high (Spearman’s rho 0.88; p<0.0001). Each point in Figure 2 rep-resents an individual department.

Furthermore, the correlation between IF and single major components of altmetrics such as Facebook (Spearman’s rho 0.80; p<0.0001), Twitter (Spearman’s rho 0.90, p<0.0001) and Mendeley (Spearman’s rho 0.90, p<0.0001) was very good.

Analysis of single departments

Looking at the impact of different departments we fo-cused on the Oncology Department to see where a single de-partment with a typical output of relevant articles would fit in our analysis compared to other departments.

Figure 3A shows the same correlation as Figure 2, but highlights where the Oncology Department (marked in red in the graphs) stands and where the outliers stand. Figures 3B, 3C and 3D show where the Oncology Department and the outliers stand when only Facebook, Mendeley and Twitter, respectively, are considered.

Interestingly, while the Oncology Department seems to closely follow the trend of most departments, 2 departments had different altmetrics scores from the others: the Throm-boembolic Disease Unit, which had higher Facebook, Twitter and Mendeley scores, and the Neurosurgery Clinic, with a high Facebook score. Also the Internal Medicine Unit (with papers about celiac disease) and the Hospital Management Department (particularly with a paper on exposure to pesti-cides or solvents and risk of Parkinson disease) had Facebook scores higher than expected on the basis of the IF. Besides these few, highly specific examples, there was very good and statistically significant agreement between altmetrics and IF.

Discussion

Evaluating the importance of an article is becoming ever more important for researchers who lack the time to read all relevant papers. Traditionally, bibliometrics is the application of quantitative analysis and statistics to publications such as journal articles and their accompanying citations. The newly

Fig. 2 - Correlation between the sum of altmetrics scores and the

sum of IFs relative to all the articles published in 2013 calculated for each of the departments of our institution.

Fig. 3 - Highlighting where the Oncology Department (in red in the

graphs) stands (A). Correlation between the sum of Facebook wall scores and the sum of IFs relative to all articles published in 2013 calculated for each department of our institution (b). Correlation between the sum of Mendeley reader scores and the sum of IFs relative to all articles published in 2013 calculated for each depart-ment of our institution (C). Correlation between the sum of Twitter scores and the sum of IFs relative to all articles published in 2013 calculated for each department of our institution (D).

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developed altmetrics have proven to be user friendly, graphic, self-explaining also for nonspecialized readers, rapidly evolv-ing and interactevolv-ing with media and public or users.

Institutions are also very interested in implementing the use of altmetrics data. For example, the Dublin Business School and the University of Tor Vergata will integrate PlumX within the school’s institutional repository (IR), so that the im-pact of any research output added to the IR can be measured by PlumX. Many others institutions – such as the University of Cambridge, the University of Manchester, the University of South Australia and the University of Aalto in Finland – are using Altmetric.com for the evaluation of their impact, indi-cating that the faculty’s research activity is an integral aspect of program accreditation and validation.

In our study, we documented a very good correlation of altmetrics with standard bibliometric indexes both at the institutional and departmental level, as already shown by Costas et al (13) and in a meta-analysis by Bornmann (14). A high percentage of manuscripts had their own altmetrics score, consistent with data shown in the biomedical field by Haustein et al (15, 16).

Altmetrics could act as a reliable tool in evaluating de-partments, and could be considered in addition to traditional metrics when managing funding activities. For this reason, altmetrics can greatly help institutions understand their im-pact on society. They may also help researchers and institu-tions to maximize the success of their own research efforts.

In our institution, a high score was obtained by many items, both within the research community (e.g., Mende-ley readers) and among the general public (e.g., Twitter and Facebook users). Interestingly, in many cases, hot topics like thromboembolic disorders, neurodegenerative diseases and celiac disease have a greater impact on the general public than on the research community. So it is becoming more and more evident that alternative metrics may play a crucial role in helping society as well as patient communities to re-trieve reliable information. Thus, together with knowledge-able scientific journalists, they could contribute to spreading relevant scientific results for the scientific education of the public. They may also highlight the value of the most success-ful research programs to their institutions, since altmetrics measure the impact in real time (17). Showing how research is relevant to the general public is useful especially for institu-tions and foundainstitu-tions funded by public money, like the one taken into consideration in this study.

Limitations of altmetrics and implications of the study

There are certain limits that should be considered in the use of these new metrics. First, when dealing with citations there is no distinction between positive and negative com-ments and this fact could distort an article’s score. In the same way, social media may be particularly vulnerable to “gaming” by commercial services that sell Facebook posts, tweets or blog mentions (18, 19).

Another critical issue is that there is currently no stan-dard for reporting altmetrics. For this reason, last year the National Information Standards Organization (NISO) re-ceived a grant to develop a standard in the field of these new metrics (20).

Last but not least, altmetrics – like bibliometrics before – need time: the concept of these metrics, together with the development and changes of social media, is still evolving and not yet fully understood by the scientific community.

The data from our study are from a single institution, re-sulting in a smaller sample size compared to other studies. However, the in-depth analysis of various departments in a single institution reduces the heterogeneity inherent in data coming from different institutions, and allows to perform an analysis of a real-life situation and to measure in a pragmatic way the impact this new metric should have in addition to the traditional ones.

Conclusion

The data resulting from this study indicate that altmetrics are useful and may well be considered as reliable metrics for measuring research. Furthermore, they could actually rep-resent an interesting and relevant complement to citations, providing institutions and researchers with a new framework to evaluate not only their academic influence but their so-cial impact. Together with traditional metrics, they could be a useful tool in guiding decision makers when funding public research. Nevertheless, further investigations are still needed to explore and understand how these new indexes can be used in the evaluation of research.

Disclosures

Financial support: None.

Conflict of interest: The authors have no conflicts of interest related to this article.

References

1. Garfield E. The history and meaning of the journal impact fac-tor. JAMA. 2006;295(1):90-93.

2. Hirsch JE. An index to quantify an individual’s scientific re-search output. Proc Natl Acad Sci USA. 2005;102(46):16569-16572.

3. Priem J, Piwowar H, Hemminger B. Altmetrics in the wild: us-ing social media to explore scholarly impact. Published March, 2012. Available at http://adsabs.harvard.edu/abs/2012arXiv 1203.4745P. Accessed February 14, 2016.

4. Priem J, Hemminger B. Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday. 2010;15(7). 5. Torres-Salinas D, Cabezas-Clavijo Á, Jiménez-Contreras E.

Alt-metrics: nuevos indicadores para la comunicación científica en la Web 2.0. Comunicar: Media Education Research Journal. 2013;21(41):53-60.

6. Priem J, Taraborelli D, Groth P, Neylon C. Altmetrics: a manifes-to. Published October 26, 2010. Available at http://altmetrics. org/manifesto. Accessed February 14, 2016.

7. Priem J, Groth P, Taraborelli D. The altmetrics collection. PLoS ONE. 2012;7(11):e48753.

8. Priem J. Twitter. Published September 28, 2010. Available at https://twitter.com/jasonpriem/status/25844968813. Accessed February 14, 2016.

9. Cave R. Overview of the Altmetrics landscape. In: Bernhardt BR, Hinds LH, Strauch KP. Accentuate the positive! Charleston Conference Proceedings, 2012. Against the Grain Press 2013; 349-356.

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10. Adie E, Roe W. Altmetric: enriching scholarly content with article-level discussion and metrics. Learn Publ. 2013;26(1): 11-17.

11. Rodgers E, Barbrow S. A Look at altmetrics and its growing sig-nificance to research libraries. Hdlhandlenet, 2013. Available at http://hdl.handle.net/2027.42/99709. Accessed February 14, 2016.

12. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159-174.

13. Costas R, Zahedi Z, Wouters P. Do “altmetrics” correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. J Assoc Inf Sci Technol. 2015;66(10):2003-2019.

14. Bornmann L. Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics. Scientometrics. 2015; 103(3):1123-1144.

15. Haustein S, Thelwall M, Lariviere V, Sugimoto CR. On the re-lation between altmetrics and citations in medicine (RIP). In:

Hinze S, Lottmann A, eds. Proceedings of the 18th Interna-tional Conference on Science and Technology Indicators (STI), Berlin, Germany, September 4-6, 2013;164-166.

16. Haustein S, Peters I, Sugimoto C, Thelwall M, Larivière V. Tweet-ing biomedicine: an analysis of tweets and citations in the bio-medical literature. J Assoc Inf Sci Technol. 2014;65(4):656-669. 17. Galligan F, Dyas-Correia S. Altmetrics: rethinking the way we

measure. Serials Review. 2013;39(1):56-61.

18. Lapinski S, Piwowar H, Priem J. Riding the crest of the altmetrics wave. How librarians can help prepare faculty for the next gen-eration of research impact metrics. College & Research Libraries News. 2013;4(6):292-300.

19. Barbaro A, Gentili D, Rebuffi C. Altmetrics as new indicators of scientific impact. Journal of the European Association of Health Information and Libraries. 2014;10(1):3-6.

20. Alternative Metrics Initiative - National Information Standards Organization (ISO). Available at http://www.niso.org/topics/tl/ altmetrics_initiative/. Accessed February 14, 2016.

References

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