Here is a good idea and smart approach to content overload. In 2008 there was more content produced through the Web than the entire previous years. Then it was repeated again in 2009. Search is a partial solution but Google’s approach was created before the huge explosion of content through social media and is subject to SEO manipulation. We need to go beyond simply search to filter down content to find what interest us.
IBM has taken a novel approach through its experimental application, Social Lens. I recently attended a media session at IBM and got a demo of the Social Lens application among others (see 2010 Update on IBM Social Software Efforts: Part Two). The Center for Social Software has created and number of interesting apps. I recently followed up with Michael Muller and Elizabeth Daly for a more in-depth discuss of Social Lens.
Social Lens lets the user set the stage and then provides automated support that the user can continue to refine. To set a lens, users first define people, resources, and communities that form their core interest area. The application is currently operating with the IBM Lotus Connections environment but it appears that the concept could be applied in other contexts. Here is a list of people.
Now that the user has set the foundation, Social Lens builds on this start by suggesting other people, resources, and communities that related to the original picks. These auto-generated selections form the second tier of content sources. The user can either promote them into the primary core of content sources or drop them altogether. Here is a list of initial communities with an additional one.
Content from the primary core has a slightly higher ranking if the user decides to the narrow the lens. You can to cast a wide net and include all the selected sources or narrow down the focus to only get content from the primary core group. You can also continue to fine tune the primary and secondary content sources. Here is a sample social lens.
Content is delivered through a time ordered activity stream that shows the new stuff coming out of the selected group. You can see a sample activity stream below.
This is an experimental application and IBM has conducted research on its effectiveness. They compared the perceived “interestingness” of content served up through Social Lens with content from other sources, one that is a personalized filter and the other is a general one. Social Lens scored higher on both interestingness and also on the “relatedness” of the second-tier auto-generated content. It also generated a large amount of useful content that the user might not have been seen otherwise.
I really like what they are doing here. It offers the user a role and then makes use of what a computer can do best to amplify the user’s selections. Here is another description that appeared in the Technology Review.