ReadWriteWeb

Filtering the Real-Time Web

The massive flow of information delivered by the emerging real-time web has some important inherent value, but building added value through intelligent extraction of information from that flow is the next step that online services are beginning to take. Social interaction design specialist Andrian Chan explored what this might look like in an excellent article today titled Activity Streams: Content and Flow that we'd like to highlight as our Real-Time Web Article of the Day.

"I think there are two distinct trends at work here," Chan writes. "One, the popularity and adoption of the stream as a form of social conversation. And the other, the conversion of realtime information into value that can be consumed outside the stream. Or to put it another way, the value of being in the flow, and of watching it from the river's edge."

In preperation for our forthcoming ReadWrite Real-Time Web Summit on October 15th and the publication of a major research report on the topic, we're highlighting one great article on the topic each day and briefing key companies working in this space. Chan's articulation of the things made possible by systems that filter the flow closely resembles what we're hearing from others we're talking to - filtering to add value is going to be key.

We're big believers in the value of the full, noisy flow as well - but the value latent in filtering is just as important.

"We can easily imagine a wide range of activities that are currently page or site-based being handled instead by the stream," Chan wrote today.

"Invitations, meeting requests, buying and selling, questions/answers -- these and much more could be transacted by means of messages 'off the page' and extracted or sorted out of streams by smart clients or aggregators. Analytics companies will have a gold mine of relationship data to scrape and visualize, for example, for use by those who want to see how influencers reach their audiences, around what topics, how quickly, with what redistribution, and so on."

"The primary goals of interaction models used around the flow involve separating content from the conversational stream, extracting meta data where possible, assigning categories and embedding within content structures and navigational systems. Then the social challenge becomes making it accessible (search, browse, and categorization) and making it socially interesting (lists, rankings, votes, etc)."

Chan's full post goes into greater detail about both the value of the whole stream and what filtering could look like.

Chris Messina told us something similar in an interview today. "The river of news model doesn't have the handles regular people can grasp," he said. "It needs to be delivered in a way that respects your time, enhances the content or makes it easier to consume the content. My mom would like iPhone push notifications of pictures of me, for example, so she could comment in reply immediately. I hope this information can be made more actionable."

How do you picture services applying or enabling filtering to add value to the flow of the real-time web? Maybe you're a service provider working on this and maybe you're a consumer/participant excited about the possibilities. Let us know in comments, and if you can we'd love for you to join us for face-to-face conversations like this at the ReadWrite Real-Time Web Summit.


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