In the early days of the Web, librarians would often compile directories of “trusted sites” on a range of important topics. In fact, Yahoo! has its roots in what was essentially a human-edited directory of online content — then called David and Jerry’s Guide to the World Wide Web. These are early examples of online content curation.
A content curator is someone who finds, groups, organizes and shares the best and most relevant content on a specific issue. In the past, content curation was largely the domain of small groups of professionals.
Today, services like Tumblr have begun to attract part-time, amateur content curators by making it easier than ever to “publish” the interesting things you find online. While these services have undoubtedly brought content curation to new audiences, the time and effort involved remain significant barriers.
Further technological innovation is needed to lighten the burden of the entire process of finding, organizing, and grouping, and sharing content.
Taking the work out of content curation
One problem with existing tools is that they force people to work at the level of individual pieces of content. Given the flood of content on the Web, this approach requires a lot of manual labor on the part of a content curator. If the manual approach is the only one available, content curation is doomed to be a niche activity.
A new system is needed — one that puts raw computing horsepower in the hands of content curators to help them get the job done orders of magnitude faster than they can today.
Content curators want to spend their time focusing on their editorial vision, pulling together the ideas that matter most to them and their audience. They likely don’t want to wade through hundreds of pages of search results and feeds, painstakingly organizing what they find.
The key, then, is to enable content curators to quickly express their ideas, indicate a few sources to get content for those ideas, and let computers do the hard work of finding and organizing content around those ideas. The final step is for the content curator to vet the work of the computer, modifying the results as they see fit to give the results that “human” touch.
With a product like this, content curation could become easy enough — and fast enough — that anyone could do it.
Primal’s technology for understanding individual interests and Web scale content filtering takes much of the grunt work out of content curation.
To learn more, check out our developers site.