Live Web, Real Time . . . Call It What You Will, It’s Gonna Take A While To Get It

This guest post is written by Mary Hodder, the founder Dabble. Prior to Dabble, Hodder consulted for a number of startups, did research at Technorati and wrote her masters thesis at Berkeley focusing on live web search looking at blog data.

Real time search is nothing new. It is a problem we've been working on for at least ten years, and we likely will still be trying to solve it ten years from now. It's a really hard problem which we used to call "live web search," which was coined by Allen Searls (Doc's son) and refers to the web that is alive, with time as an element, in all factors including search.

The name change to "real time search" seems a way to refocus attention toward the issue of time as an important element of filters. We are still presented with the same set of problems we've had at least the past ten years. None of the companies that Erick Schonfeld pointed to the other day seem to be doing anything differently from the live web search / discovery companies that came before. The new ones all seem to be fumbling around at the beginning of the problem, and in fact seem to be doing "recent search," not really real time search. While I'm sure they've worked really hard on their systems, they are no closer than the older live web search systems got with the problem. All the new ones give a reverse chron view, with most mixing Twitter with something: blog data, other microblog data, photos, creating some kind of top list of recent trends. Some have context, like a count of activity over a period of time, or how long a trend has gone on or a histogram (Crowdeye) which both Technorati and Sphere experimented with in the early years. Or they show how many links there are to something or the number of tweets. All seem susceptible to spam and other activities degrading to the user experience and none seem to really provide the context and quality filters that one would like to see if this were to really work. All seem to suffer from needing to learn the lessons we already learned in blog search and topic discovery.