BIBLIOMETRIC TOOLS: UCT LIBRARIES

Bibliometrics – quantitative analysis of scholarly literature

“Quantitative analysis of literature of a subject domain as represented by bibliographic entities such as keywords, classification codes, authors and citations.” (Willet, 2008)

Individual Researchers can use Bibliometrics to determine:

Research impact of published work: Various indices to measure and or track one’s own or other’s

research.

Collaboration: Identify research partners / potential for cross-disciplinary work

/ potential for national or international collaboration

Dissemination: Journal analytics - Where to publish for maximum visibility / analyze and compare journal

information / track how research is received by others

Bibliometric evaluation may be required for: Advancement:• Grant proposals, • NRF Rating Applications, • Curriculum Vitae, • Performance Reviews

Institutions can use Bibliometric tools to make informed decisions:

• Hiring or promotional purposes• Allocate funding appropriately• Policy decisions• Track emerging trends and find niche

research areas• Compare and benchmark impact of

research with other institutions• Find collaborating partner institutions

nationally, internationally, within an institution

• Track corporate / academic collaboration

How can I find an institutions’ disciplinary focus?How can I see how institutions collaborate geographically?What are my institutions research strengths?Who are the most productive authors and institutions in a particular discipline?

•Web of Science (Thomson Reuters)•Includes Journal Citation Reports for journal metrics

•Scopus (Elsevier)•Includes SCImago journal analytics / rankings

•SciVal (Elsevier)•High level Overview of research performance, Benchmarking& Collaboration

•Google Scholar•Uses citation information for bibliometric reporting

The main databases with multi-disciplinary coverage that can be used to track bibliometric data:

UCT Libraries subscribes to databases that can help you determine:

Journal Impact factor – a metric that reflects the impact of a journal over a number of years - use the database ‘Journal Citation Reports’ (Web of Science)

Journal Rank – a metric that reflects the prestige value of a journal relative to discipline - use ‘SCImago’ (Scopus SNIP & SJR.) or ‘Journal Citation Reports’

Comparison of Journals – use ‘Journal Citation Reports’ or ‘SCImago’

Citations per paper – use Web of Science, Scopus, Google Scholar

Bibliometric tools also offer Productivity metrics - Author metrics, Scholarly output, h-Indices (h, m, g)

Determine my H-index (Citation based ranking)

Web of Science – productivity indicators, h-index

Scopus – productivity indicators, h-index

SciVal – productivity indicators, h,m,g indices and also offers Comparison of indices – e.g. Scholarly Output vs Citation Count vs h-indices

Google Scholar – h-index

A word of caution:

Do not compare h-index across disciplines – always compare apples with apples – different disciplines have different citation behaviours.

Besides informed peer review, scholarly impact can partly be determined by using bibliometric indices (Norris and Oppenheim, 2010)

Attention metricsLook at the quantitative measures of the amount of attention someone’s work is getting.

The impact of work is tracked using social media, twitter, blogs, related news outlets, downloads into Reference Managers

Examples of Alternative metrics:

Altmetrics.com

PlumAnalytics.com

Altmetrics is also available in Scopus search results

What questions you can ask

Which journal titles are available to publish in in my field?Which journals are publishing the ‘hottest’ papers within a discipline?Will a journal with a higher impact factor attract more citations (and reach a larger audience) than a journal with a lower JIF?

Citation reports - for a variety of statistics relating to an author

Count citations - how many others have cited a particular workCited references – view all articles that have cited a particular workCitation alerts - receive an alert when someone cites a chosen workCitation maps -find related material and shared citationsRelated records – view other records that share references with a chosen work

Provides Journal metrics

SJR is weighted by the prestige of a journal. SCImago Journal Rank is a prestige metric based on the idea that not all citations are the same.Subject field, quality, and reputation of the

journal have a direct effect on the value of a citation.SJR also normalizes for differences in citation behavior between subject fields.See: http://www.journalmetrics.com/

‘Field weighted citation impact’ adjusts for the differences in citation behaviour across disciplines and puts everything on the same level.

The Field-Weighted Citation Impact is the number of total citations received divided by the total citations expected, based on the global average for the field.

• More than 1.00 means that citations are more than expected. • Less than 1.00 means the citations are less than expected.

The value of the world citation impact is 1. So this is showing you that over a 5 year period UCT’s citation impact was 1.74. Citations are 74% more than expected based on the global average.

SciVal Overview moduleCitations tab – highlights institutions citation impact.

Scopus & Web of science offer author disambiguation and allows you to search by unique identifiers

Create your own Researcher ID (Web of Science)

Create your own ORCID ID - Open Researcher & Contributor ID

Find this at: http://orcid.org

Tips for researchers: Create a Unique researcher identifier - to distinguish you from every

other researcher

Limitations of Bibliometric indicators

Understanding how the metrics were constructed is essential before making an interpretation.

Citation analysis should always be considered in conjunction with the views of scholarly peers

Citation behavior varies across discipl ines so it is unwise to compare metrics across discipl ines. Compare apples with apples.

Always consider the context when applying metrics.

Publication behavior & Self citation behaviour differs across discipl ines

Never use only one metric to answer a question – triangulate

Some citation databases al low for comparisons – e.g. SCImago Journal Rank normalizes for differences in citation behavior between subject f ields.

Field Weighted Citation impact al lows for differences in citation behavior across discipl ines.

Bibliography

Egghe, L. 2006. Theory and practise of the g-index. Scientometrics. 69(1): 131-152. Available: http://dx.doi.org/10.1007/s11192-006-0144-7.

Falagas, M.E., Pitsouni, E.I., Malietzis, G.A. & Pappas, G. 2008. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses. Faseb Journal. 22(2): 338-342.

Gumpenberger, C., Wieland, M. & Gorraiz, J. 2012. Bibliometric practices and activities at the University of Vienna. Library Management. 33(3): 174-183. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/01435121211217199.

Harzing, A. 2010. The publish or perish book: your guide to effective and responsible citation analysis. 1st ed. Melbourne: TarmaSoftware Research Pty Ltd.

Jan, M.N. 2013. The special librarian and personalized meta-services. Library Review. 62(8): 508-524. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/LR-02-2013-0015.

Moed, H.F. 2005. Citation Analysis in Research Evaluation. Dordrecht: Springer.

Norris, M. & Oppenheim, C. 2010. The h‐index: a broad review of a new bibliometric indicator. Journal of Documentation. 66(5): 681-705. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/00220411011066790.

Péter Jacsó 2012. Google Scholar Metrics for Publications. Online Information Review. 36(4): 604-619. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/14684521211254121.

Shari, S., Haddow, G. & Genoni, P. 2012. Bibliometric and webometric methods for assessing research collaboration. Library Review. 61(8): 592-607. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/00242531211292097.

Skelly, L. 2014. How to draw up a bibliometric report: a guide for academic librarians. (Unpublished).

Sidiropoulos, A., Katsaros, D. & Manolopoulos, Y. 2007. Generalized Hirsch h-index for disclosing latent facts in citation networks. Scientometrics. 72(2): 253-280. Available: http://dx.doi.org/10.1007/s11192-007-1722-z.

Willett, P. 2008. A bibliometric analysis of the literature of chemoinformatics. Ap. 60(1): 4-17. Available: http://dx.doi.org.ezproxy.uct.ac.za/10.1108/00012530810847335.

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