Real-Time Web Summit today are all about creating simple, rich user experiences.How do you create filters for the real-time web? From spam filtration to relevant discovery, the "filter geeks" at the
Hashtags for Twitter are a great start, but how are the startups moving and shaking the real-time web planning on giving users filters to control their streams in ways that make the ever-increasing volumes of information more usable? From Thing Labs and Twingly to PostRank and SocialText, read on for the problems these companies and their users have encountered and how they plan to solve information overload through clever curation and cooperation.
The session was led by Twingly CEO Martin Kallstrom, who opened with a discussion about hashtags. But one of the best things about both the unconference format and the intellectual cachet of Silicon Valley is illustrated by what happened next.
Thing Labs' CEO, Jason Shellen, interrupted to insist that we broaden the discussion to include the entire real-time web and all possible examples of filtration systems, not just Twitter and not just hashtags. From there, the conversation exploded into an executive-level goulash of how to make the real-time web useful.
The overall poverty of the user experience was generally deplored. "We hear from our users about what they want," said Shellen. "People say, 'Just show me the important stuff.'" The current state of real-time UXes allows for a lot of opportunity - the opportunity to make this iteration of the Internet simple for new users as well as appropriately complex for powerusers, unlike what we've all seen with RSS, which remains an underused geekcore feature.
The spectrum of data and metadata was brought up several times, as well. Keywords (e.g., hashtags) are a good start, but richer metadata would allow for filtration by sentiment or location. For example, a user might want to see blog posts about Obama's winning the Nobel Peace prize from right-leaning sources only. Or I might want to see pictures posted by people within 100 feet of me while I'm at the Real-Time Web Summit.
Overall, having the author, location, time, sentiment, and keywords automatically applied to user-generated data could lead to much richer streams with built-in filtering opportunities, both filtering content out as well as discovering new content and sources.
Another major point of emphasis for this session was the fact that a critical mass of users generally leads to the best filtering: Large datasets create very specifically defined problems and finely tuned filtration. Unfortunately, the startups involved in the real-time web often have smaller user bases than would be desired; there is simply not enough data generated by the users of the individual services. But what if all that user data was combined somehow?
"Right now," said Kallstrom, "people doing startups trying to combat information overload are mostly focused on finding high-quality signals. It's a very hard problem. The highest quality for the end user is achieved by moving from competing on gathering the signals to creating a great user experience through more open data."
One participant suggested publishing user activity to open-source the problem of how to filter real-time data. Many other participants agreed that the problem requires collaboration, data portability, and open standards between all the companies in the room and beyond. Such collaboration would make all real-time products better and lead to better experiences for users.
Then again, better filtration could be a real-time holy grail, a solution worth selling. And when the question of money comes up, will these startups be willing to sacrifice a theoretical goldmine to collaborate on a user-friendly solution?