Research Method: Webometrics

The Calculation of Web Impact Factors

Joel PippinJimmy Wilson

What are Webometrics?

Nomenclature Clarification –

Webmetrics = Webometrics = Cybermetrics = Web Bibliometrics

A Caveat:“Web Metrics” or “Webmetrics” (without an “o”)

- quite often refers to website service and application monitoring- marketing and systems administration

While not a completely unrelated subject, this type of Webmetrics is not really the web-based offspring of bibliometrics that we are discussing today.

What are Webometrics?

Webometrics Defined –

Whichever name you use, Webometrics is the child of Bibliometrics (formerly “statistical bibliography”)

Bibliometrics is the encompassing term for the correlated fields of Infometrics, Scientometrics, and Technometrics

These fields are linked by their emphasis on knowledge transfer and new contributions to the evolving body of knowledge in the sciences/information fields.

Bibliometrics can be generically applied to a gambit of measurements and statistics. It is most often applied to citation/publishing behavior.

Webometrics is less vague (once you get past the nomenclature issue) – it considers linking behaviors between websites and web publications.

Article Background

Web Impact Factor studies use hypertext links to study the influence of sites

Impact Factors show the “relative attractiveness” of sites on the web at a given point in time

It is important to realize that these studies are from a given point in time; the web is dynamic and these Impact Factors are constantly in flux

Problem Statement

Bibliometrics – uses self-citations + external citations to find Journal Impact Factors

Webometrics – uses self-referential links + external links to find Web Impact Factors

So, can we effectively isolate and estimate the Impact Factors for the web (Web-IF or WIFs)?

Are WIFs as feasible and reliable as JIFs when studying hypertext link structure in web sites?

What provides more reliable calculations - national web sites or institutional web sites?

Data Analysis

A series of studies done during March of 1998 by Peter Ingwersen at the Centre for Infometric Studies in Copenhagen, Denmark.

Each study lasted ~1.5 hours and repeatedly observed search behavior at 120 second intervals over that timeframe.

Concentrated on seven small/medium national sites and four top level web domains.

Used Alta Vista’s advanced search mode (1998) for retrieval- adv. search mode uses Boolean search strings and provides exact number of sites found- large scale sampling (unknown run-time limitation and unknown exhaustivity)

Data Analysis, cont.

Basic formula: self-LP ext.-LP = link-P (LP = Linking

Pages)

Order and search elements in Boolean AND were assumed to not influence outcome: a b = b a

However, this outcome does differ slightly according to the researchers, possibly skewing the results.

Data Analysis, cont.

Results

The researchers were able to successfully calculate Web Impact Factors

IFs were more reliable for national web sites according to the results of the study

Institutional website calculations should be analyzed with caution…

Possible Bias

Servers that registered generic domains could be located outside of the U.S.

Servers could block the access of web crawlers

Aforementioned (and admittedly incorrect) assumption that search term order doesn’t matter

Search engine run-time limits and exhaustively

Conclusions

Usefulness Web-IFs are calculable Leads to more research to evaluate the

trends in the data

Sherbet dish

Summary

Scientometrics Infometrics Technometrics Bibliometrics Webometrics (Cybermetrics)

Are just slight variations on a theme…Tracking, studying, and documenting knowledge transfer across publishing mediums and fields of study.

Issues to Deal With…

Web Impact Factor behavior is also proving manipulable by marketers.

Linking by the hundreds wherever they can…- blogs- newsgroups, bbs

- their own otherwise useless trash sites- well crafted but useless trash sites (in hopes of not being blacklisted by search engines)- anywhere else (especially on sites that have status) they can place links to peddle their goods.

Things that make you go hmm…

When googling “bibliometrics webmetrics”…The first returned link is to a site at the University of Texas…http://www.gslis.utexas.edu/~palmquis/courses/biblio.html

Hmm… it appears to be a page by Dr. Palmquist’s. (see ~palmquis in link)

Considering what we know of Web Impact Factor studies, if we assume that the first hit is the “most linked by other sites” link, then is Dr. Palmquist responsible for change in the nomenclature – from the “webometrics” found in older journal articles to the “webmetrics” that is showing up in bibliometrics discussions recently?

Questions?