Last time, I offered an overview of social search, touching on the pros and cons of injecting human judgment into what’s traditionally been a heavily algorithmic process. Today, I’ll map out various approaches to social search and some of the key players in each area.
Most major Web search services are dabbling with social search. Smaller companies are creating social search tools as the core foundation of their business. Most social search services have some distinguishing technology or approach. What follows isn’t a comprehensive overview of what’s out there. Rather, it’s a sampler of what’s going on in the space.
Although all these services can bring interesting content to the surface, they tend to reflect the biases and interests of their most avid users. And since even people with a lot in common can also have widely divergent interests, they often contain noisy results that may not be relevant.
Shared Bookmarks and Web Pages
One of the first types of social search services to emerge sought to leverage the power of shared bookmarks. The idea is if people save a particular page as a bookmark or favorite, they effectively vote for that page. This is fundamentally the same idea behind Google’s PageRank, but it counts the votes of Web users rather than Webmasters.
In the Web’s early days, directories were the most popular information-finding tools. Directories are compilations of Web site pointers created by humans. They typically write descriptions of entire Web sites distilled into pithy one- or two-sentence descriptions.
As the Web exploded in size, labor-intensive directories fell out of favor, while algorithmic search engines, which could easily catalog many billions of individual pages, won approval. But the open-source model of allowing numerous volunteers to collaborate has saved the directory model.
Collaborative directories have limited scope compared to algorithmic search engines, such as Google, Ask, and MSN. But limited scope also means most entries are high quality; you needn’t worry too much about spam creeping into results.
The Open Directory Project (ODP) is the original collaborative directory. ODP is a great resource but has suffered from years of neglect by its owner, AOL. Newer collaborative directories with fresher, often potentially better, results include PreFound and Zimbio. Wikipedia, even though it’s ostensibly an encyclopedia, contains so many links to authoritative Web pages that it should also be considered a collaborative directory.
Tag engines, or “taggregators” for want of a better word, tend to focus on blog and feed-based content. These services cluster content based on labels users have created to describe it. Though tags can be useful, particularly for things like photos, music, video, and other non-text content, tags can also easily be misused, with inaccurate, ambiguous, or even misleading words.
Personalized verticals are a relatively new approach to social search. These services make it easy for anyone to create a specialized search engine focusing on a relatively narrow topic. Just define the topic area you’d like the search engine to focus on, then do a bit of tuning once the search engine has built the specialized index.
You can also include your own ads in search results for your personalized search engine, allowing you to monetize your efforts and compete, at least on a small scale, with the major search services.
Social Q and A Sites
Q and A sites are yet another category of social search sites that have been around forever. Most public library sites offer “Ask A Librarian” services, which allow you to post questions to librarians and get answers by e-mail, IM (define), or SMS (define). Online forums and bulletin boards also allow people to post questions and get answers.
Google started its Answers service several years ago. Want an answer to just about any question you may have? Simply post it and offer a bounty of $2 to $200. You’ll get consideration from an army of Google-qualified volunteers who will research your question for you.
Tagging allows content creators to write descriptive labels for their material. But, as I mentioned earlier, tags aren’t always accurate or even helpful for users. Sometimes you want recommendations from people who have already consumed the content and found it interesting, useful, or entertaining.
Collaborative harvesters are a relatively new breed of tools that tap into their users’ collective wisdom. When a user finds something interesting on the Web, he nominates it for consideration by other users. People then vote on the content, and any content that garners enough votes gets pushed forward as a recommended source for the rest of the community.
Among the more popular of these collaborative harvesting services are digg, Netscape, Reddit, and Tailrank. If you really like the idea, a site called popurls aggregates all the top recommendations from these and other Web sites, including Flickr and YouTube, on a single page.
Want more search information? ClickZ SEM Archives contain all our search columns, organized by topic.