EXPERT ADVICE

Social Search: What It Is and Why It’s Not Going Away

Don’t look now, but social search is pervasive. It’s taking hold in large part because the Web itself is changing.

What is social search? Broadly speaking, social search enables the masses to have greater influence on the results of a search, and in so doing, enables better, more interesting and more targeted search results.

Some social search services prioritize search results based on the preferences of its entire user base, while others segment users to provide results that are more closely tailored to a particular user. Still others allow users to organize content into collections which can then be found by searchers. Whatever the form, the common thread with social search services is that users themselves have greater control over the results.

Traditional vs. Social

Is social search fundamentally different than the traditional search engines like Google and Yahoo? Some have drawn a clear line separating Google, et. al. and social search. However, in fact, the most common example of social search is Google. Google’s PageRank algorithm relies heavily on the number of sites linking to a particular site, and the popularity of those sites that are doing the linking in prioritizing the search results. So, PageRank incorporates a form of social search, although it’s based more on the explicit actions of webmasters than on the implicit actions (clicks) of the searchers themselves.

Sometimes traditional search engines prove to be less than effective to searchers. To wit: 41.2 percent of users report that general search results are often not directly relevant to queries, and 18 percent leave a search engine without having found the information they’re seeking, according to a recent study by JupiterResearch. This problem also exists for business professionals: Only 40 percent of professionals are satisfied with general search engines, with just 11 percent of users reporting that they always found what they were looking for on the first attempt.

Part of the issue with traditional search engines is that they are frequently “gamed” by marketers. In other words, Web sites that do the best job of SEO (search engine optimization) — and not those that are most popular with searchers — rise to the top of the search results. Search engine companies actually publish best practice techniques for SEO, you can find recipes on Wikipedia and there are plenty of other places where you can learn the ropes, including a site named “Search Engine College.”

So, one of the side effects of the PageRank algorithm is that clever search engine marketers often have a disproportionate amount of sway over the results. Partly in response, a variety of social search services have been launched that give the searchers themselves more influence.

Self-Made Search

Social search sites such as Squidoo allow users to organize content into collections to create a comprehensive, well organized illustration of a particular subject. Yahoo Travel Trip Planner provides a place for travelers to create and share their itineraries. For both of these services, the search results are prioritized based on the actions of the users, and the collections that are most popular with searchers naturally rise to the top.

Contrasted with the unrelated or redundant lists of search results typically presented by Google, the top rated results usually present well though-out collections of content that offer a comprehensive view on a topic (or a trip). In this regard, these types of social search results are more akin to a Wikipedia entry than a traditional results page on a search engine.

Social search can also be used to personalize results for individual users instead of providing “one size fits all” results to a query. Consider Stumbleupon, Pandora and Netflix, for example. Each of these sites employ elements of social search. Users rate Web sites, songs and movies, respectively, based on their individual preferences.

Then by tapping into the (anonymized) online behavior of similar users (or “collaborative filtering” in the industry parlance), the sites present new Web sites (or songs or movies) that are tailored to each user. Of course, the irony in this is that probably no company has better online personalization data than Google. To date, Google has been focusing their efforts on using this data to serve more personalized ads. When will Google turn their attention to personalizing search results?

Participation Inequality

For any service that incorporates social search, there exists a potential problem — that the results are not useful without significant numbers of users providing their input. Jakob Nielsen described this well with his work on participation inequality, in which he observes that 1 percent of members of an online community are content creators, 9 percent are participants and 90 percent are lurkers. The challenge, then, is to encourage useful contributions not only from the usual creators but to also turn the 90 percent who are lurkers into “accidental” creators, getting them to share their likes and dislikes with the larger community.

Services such as del.icio.us and Foxmarks have cleverly addressed this issue by inferring popularity through their users’ actions of bookmarking and tagging content. Other users can then find the most commonly bookmarked (and hence the most popular) links on any topic.

We’re in an exciting time, where social search is both prevalent and rapidly evolving. Finding the right mix that returns the most representative results based on the desires of users, not marketers, is sure to win out in the long term. While only a cave dweller would count Google out of the survivors, which other services will prevail is anyone’s guess. However, one thing is guaranteed — as social search techniques continue to evolve, the searchers themselves will be the clear winners.


Richard Buck is the CEO and founder of Eluma, which is based in Tewksbury, Mass.


Leave a Comment

Please sign in to post or reply to a comment. New users create a free account.

More in

Technewsworld Channels