I’ll be at the Enterprise Search Summit in New York next week, participating on a panel Tuesday morning to discuss “Emergent Social Search Experience”. Our game plan as a panel is to discuss what social search is, why it matters, and how to implement it.
Obviously these are broad questions, but here are my rough notes:
WHAT: Social search means many things, but they have one common thread: improving information seeking through the knowledge and efforts other people. Back in the mid 90s, researchers distinguished between semantic and social navigation as the ability to explore information based on its objective, semantic structure, versus choosing a perspective based on the activity of another person or group of people. Perhaps the earliest instance of social search was collaborative filtering, still popular today as driver for product recommendations on sites like Amazon. But social search is much more than collaborative filtering. Building on the 90s vision of social navigation, we can give users full control over a social lens through which to view information, e.g., show me the local restaurants where women in my mom’s demographic like to eat brunch. Social search also includes explicit and implicit collaborative approaches, such as finding an expert to help you with a search, or building shared knowledge management artifacts that increase the collective efficiency of information seeking.
WHY: The “why” of social search depends on the specific aspect of social search that we’re discussing. But the common theme is this: we all know that, for a large swath of information needs, we prefer to turn to a person than to ask a machine. Sometimes that’s appropriate, and it’s a question of finding the right person to ask. But often we have no need to bother any one; we just want to borrow someone else’s perspective—or to assemble a composite perspective. There’s an efficiency gain of not reinventing the wheel, as well as an upside of discovering people (or information by way of those people) that may be valuable to you in ways you didn’t anticipate.
HOW: Again, it depends on the aspect of social search. We need rich knowledge representations that treat both information and people as first-class objects, and interfaces that let people seamlessly use both. Endeca does this by supporting record relationship navigation for multiple entity types (e.g., documents, people), as do interfaces like David Huynh’s Freebase Parallax. To facilitate collective knowledge management, we need to make contribution both easy and rewarding: the reason people don’t contribute to such systems today is that they are onerous and don’t work. Some of the work Endeca has done with folksonomies is encouraging: we found that we can productively recycle folksonomies (or even search logs) in combination with automatic text mining techniques. Finally, we need to rethink our attitudes toward privacy, anonymity, and reputation. Consumer social networks like Facebook and Twitter have shown us that users are willing to forgo privacy in order to gain social benefits. Wikipedia has shown us that a group of strangers can assemble a valuable collective knowledge store. But Wikipedia, product reviews, blog comments, etc. have shown us that the default of anonymity can undermine the trust we have in these socially constructed artifacts. As we evolve these tools—and as we work to apply them within the enterprise, we need to simultaneously work to evolve our social norms.
Those are my thoughts. But, in the spirt of social search, I’d love to reach out to experts here for ideas. If you were attending a panel about social search, specifically in the context of an event target to enterprise search practitioners, what would you want to hear about? For that matter, if you were participating on such a panel, what would you talk about? Bear in mind that the audience will consist of practitioners, not researchers, and I’ll only have one third of a 45-minute session–some of that reserved for Q&A.