A quantitative analysis of a large collection of expert-rated web sites reveals that page-level metrics can accurately predict if a site will be highly rated. The analysis also provides empirical evidence that important metrics, including page composition, page formatting, and overall page characteristics, differ among web site categories such as education, community, living, and finance. These results provide an empirical foundation for web site design guidelines and also suggest which metrics can be most important for evaluation via user studies.
%0 Conference Paper
%1 365035
%A Ivory, Melody Y.
%A Sinha, Rashmi R.
%A Hearst, Marti A.
%B CHI '01: Proceedings of the SIGCHI conference on Human factors in computing systems
%C New York, NY, USA
%D 2001
%I ACM
%K automated_evaluation imported usability
%P 53--60
%R http://doi.acm.org/10.1145/365024.365035
%T Empirically validated web page design metrics
%U http://portal.acm.org/citation.cfm?id=365035&dl=GUIDE&coll=GUIDE&CFID=34858621&CFTOKEN=31146724
%X A quantitative analysis of a large collection of expert-rated web sites reveals that page-level metrics can accurately predict if a site will be highly rated. The analysis also provides empirical evidence that important metrics, including page composition, page formatting, and overall page characteristics, differ among web site categories such as education, community, living, and finance. These results provide an empirical foundation for web site design guidelines and also suggest which metrics can be most important for evaluation via user studies.
%@ 1-58113-327-8
@inproceedings{365035,
abstract = {A quantitative analysis of a large collection of expert-rated web sites reveals that page-level metrics can accurately predict if a site will be highly rated. The analysis also provides empirical evidence that important metrics, including page composition, page formatting, and overall page characteristics, differ among web site categories such as education, community, living, and finance. These results provide an empirical foundation for web site design guidelines and also suggest which metrics can be most important for evaluation via user studies.},
added-at = {2008-06-30T20:02:47.000+0200},
address = {New York, NY, USA},
author = {Ivory, Melody Y. and Sinha, Rashmi R. and Hearst, Marti A.},
biburl = {https://www.bibsonomy.org/bibtex/25b96cc2b45e5d6233eafe59b2d842619/ewomant},
booktitle = {CHI '01: Proceedings of the SIGCHI conference on Human factors in computing systems},
description = {Empirically validated web page design metrics},
doi = {http://doi.acm.org/10.1145/365024.365035},
interhash = {aa6397edddf030d5951035a2dfdaec8a},
intrahash = {5b96cc2b45e5d6233eafe59b2d842619},
isbn = {1-58113-327-8},
keywords = {automated_evaluation imported usability},
location = {Seattle, Washington, United States},
pages = {53--60},
publisher = {ACM},
timestamp = {2008-11-17T17:10:40.000+0100},
title = {Empirically validated web page design metrics},
url = {http://portal.acm.org/citation.cfm?id=365035&dl=GUIDE&coll=GUIDE&CFID=34858621&CFTOKEN=31146724},
year = 2001
}