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Quantitive evaluation of Web site content and structure

Quantitive evaluation of Web site content and structure Describes an approach automatically to classify and evaluate publicly accessible World Wide Web sites. The suggested methodology is equally valuable for analyzing content and hypertext structures of commercial, educational and non-profit organizations. Outlines a research methodology for model building and validation and defines the most relevant attributes of such a process. A set of operational criteria for classifying Web sites is developed. The introduced software tool supports the automated gathering of these parameters, and thereby assures the necessary "critical mass" of empirical data. Based on the preprocessed information, a multi-methodological approach is chosen that comprises statistical clustering, textual analysis, supervised and non-supervised neural networks and manual classification for validation purposes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Internet Research Emerald Publishing

Quantitive evaluation of Web site content and structure

Internet Research , Volume 10 (1): 14 – Mar 1, 2000

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References (36)

Publisher
Emerald Publishing
Copyright
Copyright © 2000 MCB UP Ltd. All rights reserved.
ISSN
1066-2243
DOI
10.1108/10662240010312138
Publisher site
See Article on Publisher Site

Abstract

Describes an approach automatically to classify and evaluate publicly accessible World Wide Web sites. The suggested methodology is equally valuable for analyzing content and hypertext structures of commercial, educational and non-profit organizations. Outlines a research methodology for model building and validation and defines the most relevant attributes of such a process. A set of operational criteria for classifying Web sites is developed. The introduced software tool supports the automated gathering of these parameters, and thereby assures the necessary "critical mass" of empirical data. Based on the preprocessed information, a multi-methodological approach is chosen that comprises statistical clustering, textual analysis, supervised and non-supervised neural networks and manual classification for validation purposes.

Journal

Internet ResearchEmerald Publishing

Published: Mar 1, 2000

Keywords: Neural networks; Non‐profit organizations

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