Webzeitgeist: Design Mining the Web

ACM Human Factors in Computing Systems (CHI), 2013 Best Paper Award DOI

Ranjitha Kumar

Stanford University

Arvind Satyanarayan

Arvind Satyanarayan

Stanford University

Cesar Torres

Stanford University

Maxine Lim

Stanford University

Salman Ahmad

MIT Media Lab

Scott R. Klemmer

Stanford University

Jerry O. Talton

Intel Corporation

PDF Paper

Abstract

Advances in data mining and knowledge discovery have transformed the way Web sites are designed. However, while visual presentation is an intrinsic part of the Web, traditional data mining techniques ignore render-time page structures and their attributes. This paper introduces design mining for the Web: using knowledge discovery techniques to understand design demographics, automate design curation, and support data-driven design tools. This idea is manifest in Webzeitgeist, a platform for large-scale design mining comprising a repository of over 100,000 Web pages and 100 million design elements. This paper describes the principles driving design mining, the implementation of the Webzeitgeist architecture, and the new class of data-driven design applications it enables.

Bibtex 

@inproceedings{2013-webzeitgeist
  title = {{Webzeitgeist: Design Mining the Web}},
  author = {Ranjitha Kumar AND Arvind Satyanarayan AND Cesar Torres AND Maxine Lim AND Salman Ahmad AND Scott R. Klemmer AND Jerry O. Talton},
  booktitle = {ACM Human Factors in Computing Systems (CHI)},
  year = {2013},
  doi = {10.1145/2470654.2466420},
  url = {https://vis.csail.mit.edu/pubs/webzeitgeist}
}
Webzeitgeist: Design Mining the Web

Webzeitgeist, a scalable platform for Web design mining, supplements the data used in traditional Web content mining (yellow) with information about the visual appearance and structure of pages (blue) to enable a host of new design applications (green).