science

Webometrics

Webometrics is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Webometrics rather than just read about it. In short: The science of webometrics (also referred to as cybermetrics) aims to quantify the World Wide Web to get knowledge about the number and types of hyperlinks, the structure of the World Wide Web, and using patterns. According to Björneborn and Ingwersen, the definition of webometrics is "the study of the quantitative aspects of the construction and use of information resources, structures and technologies on the Web d…

Key takeaways

Webometrics belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Webometrics to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Webometrics from memory before moving on to harder problems.

Reference excerpt

The science of webometrics (also referred to as cybermetrics) aims to quantify the World Wide Web to get knowledge about the number and types of hyperlinks, the structure of the World Wide Web, and using patterns. According to Björneborn and Ingwersen, the definition of webometrics is "the study of the quantitative aspects of the construction and use of information resources, structures and technologies on the Web drawing on bibliometric and informetric approaches." The term webometrics was coined by Almind and Ingwersen (1997). A second definition of webometrics has also been introduced, "the study of web-based content with primarily quantitative methods for social science research goals using techniques that are not specific to one field of study", which emphasizes the development of applied methods for use in the wider social sciences. The purpose of this alternative definition was to help publicize appropriate methods outside the information-science discipline rather than to replace the original definition within information science. Similar scientific fields are: bibliometrics, informetrics, scientometrics, virtual ethnography, and web mining.

One relatively straightforward measure is the "web impact factor" (WIF) introduced by Ingwersen (1998). The WIF measure may be defined as the number of web pages in a web site receiving links from other web sites, divided by the number of web pages published in the site that are accessible to the crawler. However, the use of WIF has been disregarded due to the mathematical artifacts derived from power law distributions of these variables. Other similar indicators using size of the institution instead of number of webpages have been proved more useful.

See also Altmetrics Impact factor PageRank Network mapping Search engine Webometrics Ranking of World Universities

References

Bibliography Tomas C. Almind & Peter Ingwersen (1997). "Informetric analyses on the World Wide Web: Methodological approaches to 'webometrics'". Journal of Documentation. 53 (4): 404–426. doi:10.1108/EUM0000000007205. Björneborn, Lennart & Ingwersen, Peter (2004). "Toward a basic framework for webometrics". Journal of the American Society for Information Science and Technology. 55 (14): 1216–1227. doi:10.1002/asi.20077.{{cite journal}}: CS1 maint: deprecated archival service (link) Peter Ingwersen (1998). "The calculation of web impact factors". Journal of Documentation. 54 (2): 236–243. doi:10.1108/EUM0000000007167. S2CID 27849021. Mike Thelwall; Liwen Vaughan; Lennart Björneborn (2005). "Webometrics". Annual Review of Information Science and Technology. 39: 81–135. doi:10.1002/aris.1440390110. Thelwall, Mike (2009). Introduction to Webometrics: Quantitative Web Research for the Social Sciences. Synthesis Lectures on Information Concepts, Retrieval, and Services. Vol. 1. Morgan & Claypool. pp. 1–116. doi:10.2200/S00176ED1V01Y200903ICR004. ISBN 978-1-59829-993-9. S2CID 25489497. Mazalov, Vladimir; Pechnikov, Andrey; Chirkov, Alexandr; Chuyko, Julia (2010). "Web-communicator creation costs sharing problem as a cooperative game (in Russian)" (PDF). Управление большими системами: сборник трудов. Ingwersen, Peter (2006). "Webometrics: ten years of expansion".

Illustrations

Worked examples

Example 1 — a first encounter with Webometrics

Start with the simplest possible case. Write down what Webometrics claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Webometrics before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Webometrics ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Webometrics

In research: Webometrics appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Webometrics in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Webometrics is common in secondary-school and first-year university syllabi. It links to neighbouring topics Information retrieval techniques, Information science, Web analytics, so understanding it makes those chapters shorter.
In everyday life: Look for Webometrics outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Webometrics in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Webometrics means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Webometrics out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Webometrics in simple terms?

Why does Webometrics matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Webometrics?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Webometrics.