In a recent post, Andrew McAfee offers insight into the distinction between implict and explicit content.

Explicit user-generated information is information that people knowingly and deliberately generate by contributing to online platforms. Examples of explicit information include a blog post or comment, a wiki edit, a vote or rating, a trade in a prediction market, a link, and a tag.

Implicit user-generated information is information that people unknowingly generate as they work online. It’s the digital fingerprints or traces that people leave as they follow links, look at content, consider one product then buy another, etc.

This article helped me to think about this distinction in the context of “what the user sees and does” (tools and applications) versus “underlying technologies” (collaborative filtering, visualization, mashups, data mining, etc.) It is the tools and applications that link people and content to collaborative and to co-create. It is the underlying technologies that capture and process the implicit information that provides additional explicit information into the mix. It’s a nice little ecosystem.

McAfee’s blog actually centered on the question of which is more important, implicit content (as Tim O’Reilly suggests) or explicit and came to this same conclusion: the more explicit content that is available (the more people contributing to the ecosystem), the more implicit content will become available, enriching the content environment. As E2.0 spreads, McAfee says, decision-makers who bring tools and technologies into the workplace need to be aware of (beware of) the difficulties in analyzing and using implicit data. There are privacy issues and measurement issues (are contributions individual or group? are people contributing to “look good” or to enable?). Along all of these, we’ll be wobbling for a while.