Wednesday, June 4, 2008 and Click2Tag: Lowering the interaction cost of tagging systems

Tagging systems such as and Diigo have become important ways for users to organize information gathered from the Web. However, despite their popularity among early adopters, tagging still incurs a relatively high interaction cost for the general users.

To understand the costs of tagging, for each of these systems, we performed a GOMS-like analysis of the interface and identified the overall number of steps involved in tagging. We count these steps to get a gross measure of the tagging costs:
System         Cost 6
MyWeb 7
Diigo 8
Clipmarks 10
Magnolia 6
Bluedot 6
Google Notebook 11

Tagging is a process that associates keywords with specific content. We did a rough analysis in our paper (reference below), and computed how often a keyword used by a user to tag an URL appears in the page content. We found that, on average, the chance that a tag comes from the content is 49%. This process produced a conservative estimate of tag occurrence in content, since we did not account for situations such as content changes for a given URL (e.g., dynamic content), typos (e.g., “Ajaz” instead of “Ajax”), abbreviations (e.g., “ad” instead of “advertisement”), compound tags (e.g., “SearchEngine”), and tags written in languages other than that of the content.

The following figure shows the probability distribution of a tag occurring in the page content:

We introduce a new tagging system called, which uses an intuitive Click2Tag technique to provide in situ, low cost tagging of web content. In, we bring the tagging capability into the same browser window displaying the web page being read. When a user loads a web page in his browser, we augment the HTML page with AJAX code to make the paragraphs of the web pages as well as the words of the paragraphs live and clickable. As users read a paragraph, they can simply click on any words in the paragraph to tag it. also lets users highlight text snippets and automatically collects tagged or highlighted paragraphs into a system-created notebook, which can be later browsed and searched. We're currently conducting an internal PARC beta-testing of this tool, and hope to release it for public use in the near future.

For more detail about the system we built, here is the reference:

Lichan Hong, Ed H. Chi, Raluca Budiu, Peter Pirolli, and Les Nelson. Low Cost Tagging System for Foraging of Web Content.

In Proceedings of the Advanced Visual Interface (AVI2008),
pp. 65--72. ACM Press, 2008.

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