There are social networks all around us these days, from Facebook (s fb) and Twitter (s twtr) to more targeted networks like Instagram and Path — and new ones seem to be launching every week. Do we really need another one? Bradford Cross, CEO of San Francisco-based startup Prismatic, thinks that we do, and he is doing his best to create one using the news recommendation algorithms that he and co-founder Aria Haghighi have been fine-tuning since 2011.
The next iteration of that network launches today, with a comprehensive redesign and a host of new features that are intended to stress the social side rather than the pure news-consumption side. While the older version of Prismatic allowed users to “follow” or connect with users whose interests they shared, those features are much more prominent now — and so are other aspects, such as the ability to comment and tag other users.
A network based on your real interests
When it comes to comments, Prismatic has taken an interesting tack, similar to the one that Tumblr took when it wanted to add comments: instead of just allowing people to post a random comment on someone else’s post, they have to “reblog” the original and attach their comment to that, and it appears in their own stream. Doing that, Cross says, makes it less likely that trolls will emerge, and also encourages more authentic interaction.
The new Prismatic is designed to make it much easier for users to build a network around the content that interests them, turning the “customized newspaper” model that the service started with into the core of an interest graph. While plenty of others have their sights set on the same goal, Cross believes that Prismatic is better equipped to actually do it.
The Prismatic CEO’s take on social networks like Facebook, Twitter, LinkedIn (s lnkd) and Google+ (s goog) will resonate with anyone who has become frustrated with the way that those services implement — or reflect — our social graph. In a nutshell, he believes that neither Facebook nor Twitter (nor anyone else, for that matter) does a particularly good job of reflecting your actual interests, or at least not the broad range of interests most people have.
Existing networks box you in
For most people at least, Facebook represents the part of their social graph that is made up of family and friends, the people they have ties to in the so-called “real world.” But they may have very little in common with those connections when it comes to interests such as movies, books, politics, hobbies, etc. Facebook has tried to make it easier to organize a graph around your real interests with lists and other tools, but none of them have been that effective.
Twitter, meanwhile, is also supposed to be an interest graph — because you can follow people based on what they tweet about and/or what they do. But as Cross points out, that winds up slotting most users into a fairly narrow range of interests: people follow you because you tweet about technology or politics or sports, and so you might feel a little odd deviating from that to tweet about the movie you watched or a great meal you had recently.
“Because you have to be ‘on brand,’ you wind up getting boxed in. The more you work on that, the more you can’t share stuff in other areas because it’s confusing for people. And now you’re stuck, because you have Twitter or Facebook and other than that you just have a few networks for specific things like photo sharing — there’s nowhere to share your other interests.”
It’s about relevance, and that’s a data problem
Prismatic’s solution is to use the algorithms that Cross and Haghighi have been putting together based on people’s interests since they started what would become Prismatic with a few computers and some mattresses in a condo in SoMa. As a data scientist who used to run a hedge fund and then built a data service for a startup called Flightcaster, Cross has no background in media — but plenty in understanding large data sets and how to make use of them.
After connecting the service to either their RSS feeds or a source like Facebook or Twitter, users browse through content that they have subscribed to, but also get shown things Prismatic thinks they might be interested in. As they share and/or comment on those articles, the system learns more and more about what they like and can make better recommendations — and the connections between users with shared interests gives it more to go on.
“All this stuff is basically a relevance problem — the problem of routing content to the right people. And our hope is that with the new Prismatic, you can actually start to build a sense of community around your actual interests, because the existing models aren’t working.”
Ideally, Cross says, those interests will be everything from food or architecture to music and religion — all the broad categories that users might be reluctant to dive into or share on other networks out of a concern that they might be “polluting” those specific streams with non-relevant content. Whether Prismatic actually accomplishes that will determine whether it survives, or joins the growing pile of failed social-networking experiments.
Prismatic raised $15 million in a Series A round of financing earlier this year, from a group of investors that included Accel Partners and Russian investor Yuri Milner.
Post and thumbnail photos courtesy of Shutterstock / noporn