It is hot! So hot that Google legitimized it with their recent update. Buzz is building on social search like never before, as this handy trend graph from BlogPulse indicates:
But what is social search?
According to different industry voices, social search …
“… involves combining social graph information with pure algorithmic search results.“
“… combines traditional algorithm-driven technology with online community filtering.“
“… helps you find more relevant public content from your broader social circle.“
“… is information retrieval, way finding tools informed by human judgment.“
These definitions are quite broad and varying, and the result is that so many solutions have come under the banner of “social search”. However, one thing common across these diverse set of tools and services is this: they’ve all used collective intelligence (wisdom of the crowds, if you will) in some way to improve what they present to users in the search process.
- In the early days of the Internet, DirectHit (later acquired by Ask Jeeves) watched which links users clicked through more for a given search and used that data for dynamically ranking search results based on their popularity with the community of users.
- Amazon has been a pioneer in the space of using social/community data to improve the searches for users on Amazon.com – much has been written about their recommendation engine!
- Intelliseek’s ProFusion.com engine ( a product I helped design) used an adaptive search mechanism (community usage driven) to determine what are the best sources to pick for a given query in a distributed / federated search environment.
- Wikia Search used the Wikipedia model of direct, swarm-editing of search result pages for different queries. i.e. Wikia Search users could interactively change the results on any result page, and impact what other users saw directly.
- In reality, Google has always been a social search engine, in a couple of ways. They’ve always tracked what people have liked through who / what they hyperlink to – a core to their famed PageRank algorithm. In the recent years, they’ve also included user and community contributions (in the form of social media) into their search results, with content from Wikipedia and the blogosphere impacting search results in a noticeable way.
- Yahoo has tried integration of Delicious (their social bookmarking system) into the search results.
- Presently, the buzz is all about including social network data and data from popular social tools like Twitter into the search results. Bing did it. Now Google is doing it too!
My company, Zakta, is also a recent entrant in “social search”, and we refer to Zakta as a personal and social Web search engine. Our aim is to improve informational searches on the Web.What prompted me to write this post was the recent Google announcement on social search. Our small community of users felt that Google was encroaching on Zakta’s turf, and I thought I should help clarify where Zakta fits.
First, Zakta has no turf – Google dominates all 
Second, we are trying to add value to the informational search experience of users through a comprehensive solution framework, so we don’t get into feature battles with giants that we don’t have a chance of surviving (as it is, I’ve been called “Nuts!” to start Zakta at this time, and having my tiny company enter into a feature race with the giants should surely bring me the label “Stupid” too – something I’d very much like to avoid!).
On the X-axis, I plot the Personal (focus is on the individual) versus Communal (focus is on the community as a whole) continuum. On the Y-axis, I plot the nature of information that users interact with, in terms of whether it is Disorganized (focus has been on mere collection of information) versus Organized (focus is on curation of digital information).
Using this framework, I’ve mapped a handful of social search services and tools that I’m somewhat familiar with. So, admittedly, both this framework and my characterization of these services in this framework are based on my personal viewpoint. I’d welcome comments for improvement, or other viewpoints. I hope you find this framework a useful tool to make sense of what is happening with this growing space that is simply called “social search”.
Now I can put Zakta into this context. As portrayed in this framework, Zakta is a personal Web search engine because it provides tools to deliver a personal search engine experience that puts the searcher in control.
Zakta is also a social Web search engine in many distinct ways:
- It enables a searcher to collaborate with people they trust to find, collect, organize and share information on topics of interest
- It enables a searcher to connect to others they trust and discover information relevant to their interests from the recommendations made by their trust-network
- It enables a searcher to benefit from the contributions of the community of Web users in the form of published Zakta Guides on topics of interest
- It enables a searcher to gain from the ongoing relevance ranking improvements that happen behind the scenes that take into account the signals of recommendation expressed by not only the user’s trust-network, but also the community as a whole not just on Zakta, but elsewhere on the Web
As you can see, Zakta is not as much about finding what your social network has been saying. Rather it is all about empowering you personally and helping you benefit from your trusted network as well as the community at large to improve your own Web search experience and discover useful information on an ongoing basis on topics of your interest.
As always, I’d love to get your feedback!
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