The Impending Social Search Inflection Point

Search has changed. Online consumer information retrieval has reached another inflexion point – a shift from pure algorithmic search to social search. Searchers have become increasingly sophisticated, and basic algorithmic web results are getting diluted out of most mainstream search experiences such as Google, Yahoo, Microsoft, AOL and Ask. Search is not solved. At their most sophisticated, users are still too often at a loss when executing a search. According to Jupiter, 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 were seeking.

First, there was basic algorithmic search (such as AltaVista), and then came very predictable paid search business models to fuel innovation. The industry is now maneuvering through its third era: social search. Humans are still better at some things. Relevance remains number one. Throughout the past decade, a search engine’s most critical success factors – relevance, comprehensiveness, performance, freshness, and ease of use – have remained fairly stable. Relevance is more subjective than ever and must take into consideration the holistic search experience one user at a time. Inferring each user’s intent from a mere 2.1 search terms remains at the core of the relevance challenge

Social search addresses relevance head-on. After "on-the-page" and "off-the-page" criteria, web connectivity and link authority, relevance is now increasingly augmented by implicit and explicit user behaviors, social networks and communities.

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Monthly trend chart indicating the percentage among total English-language blog posts that mentioned "social search". (Nielsen BuzzMetrics BlogPulse)

What Is Social Search?

What is social search? To paraphrase Microsoft’s Ramez Naam, it’s like every human being is a neuron, and humanity as a whole is one giant brain, smarter as a connected whole. If you can increase the ability of humans to communicate with each other, you make the whole planet smarter.

As articulated by Chris Sherman, social search is information retrieval, way finding tools informed by human judgment. Social search is people helping people find stuff using plain-language questions and answers, collaborative content harvesting, directory building, voting and ranking, sharing, tagging, commenting on bookmarks, Web pages, news, images, videos and podcasts.

The wisdom of crowds – so well articulated by James Surowiecki – is at the root of emerging information retrieval tools. Search engines are trying to resolve user intent more than content connectivity, and social search adds a new relevance layer to information retrieval in the form of context, freshness and some understanding of personal significance, personalization.

There is a shift underway from the few powerful elite to the empowerment of the masses, from few-to-many to many-to-many publishing models with an explosion in consumer-generated media. According to a Pew Internet and American Life report, 44 percent of Internet users are content creators. A significant ratio of the top 100 results for more queries are consumer-generated media such as blogs and social networks, which sounds like an invitation for social media marketers to seed more content. Internet users are getting a lot more comfortable interacting with the Web, as illustrated by MySpace’s 159,271,726 profiles (as of February 28, 2007), and the web is getting a whole lot more fluid and transparent. That said, not everybody needs to be tagging and voting for collaborative efforts to reach critical-mass impact and benefit the rest of us. There is a shift taking place from the head to Chris Anderson’s long tail.

Social search offers a new discovery paradigm. Internet search is for getting stuff done; it’s an in-and-out navigational tool. Search is also very much about discovery browsing and community-driven recommendation engines. Discovery browsing is entering a whole new navigation paradigm exemplified by companies like StumbleUpon. The traditional linear directory navigation model is broken. Most emerging social discovery engines are adopting tag clouds as navigation tools that complement the search box.

Altering Search’s Economics

Web 2.0 innovations are disruptive. The emergence of open standards, richer user experiences, content portability, social networks and communities are quite disruptive to traditional algorithmic search, and are converging toward social search. Information retrieval is changing in real time. Web 2.0 open standards have in essence separated the content we search from its format and dedicated application. More and more frequently, information is being pushed to consumers before they even have a chance to use a search engine to pull it from the Web. AJAX and Flash are turning web pages into applications, themselves becoming platform-independent mashups of RSS feeds, smart widgets, badges, and modules. Aren’t we all spending more time in aggregators, emails, and applications that automatically pull in information? Is the results page slowly getting marginalized as the web’s main information retrieval space?

Social search levels the economics. The explosion of consumer-generated media, the emergence of social search and the rise of the net’s culture of participation will eventually force a democratization of the web’s economics. Content-generating users, driving traffic and eyeballs, will increasingly share the wealth. The web is slowly but surely leveling the playing field for the rest of us in the tail. More and more personal blogs, MySpace profiles, and other communities display advertising and widgets wrapped around democratization of revenue share including payment. Consumers will eventually share the wealth in a more democratic way. YouTube announced a revenue-sharing program with authors; Bill Gates himself discussed rewarding users for searching. Content-generating users are increasingly part of the economics as well. Eurekster already goes one step further suggesting how valuable swicky communities are, estimating that some swickies could actually generate up to $30,000 a year in revenue to their owners and be worth up to $300,000 if a buyer used typical methods for valuation.

Advertisers traditionally follow consumers. Social search is already channeling significant amounts of traffic and should accelerate the pace of brand advertising dollars shifting online. Internet sentiment analysis, buzz monitoring and online reputation management could very well emerge as the next significant search marketing era after search engine optimization and paid search.

Conclusion: Search is the OS

Search is the operating system. If Web 1.0 was about getting online and Web 2.0 about collaborative networking, then Web 3.0 must be about making all of this useful and productive. In more than one way, search is the internet OS underlying most Web 2.0 applications. Search is the Internet OS connecting disjointed pieces of data hosted in totally different places and creating incremental knowledge value. Search is the Internet OS bridging communities and enabling content experiences.

Search veteran Arnaud Fischer was AltaVista’s initial lead search product manager and now is programming director with AOL Search & Directional.

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: Social | Search Engines: Social Search Engines

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  • http://www.mortgageclass.com MTing

    Arnaud,

    Very insightful post but I do have a comment regarding the direction of search…

    If social search means that the internet is going more democratic, do we not run the risk of establishing “herd mentality”? Where as with any group dynamic, there is always a small group or individual who begins to take over. Then the rest of the group simply follows along. Does that necessarily mean that “the wisdom of crowds” is a good thing?

    I am also not entirely sure how this movement is “slowly but surely leveling the playing field for the rest of us in the tail.”

  • http://searchistheos.blogspot.com/ Arnaud fischer

    MTing, right on! Glad you enjoyed the piece. James Surowiecki actually defines The Wisdom of Crowds around a few principles. The principle of opinion Independence is critical. There cannot be influence or as Surowieki explains, “cascading” effect from one to the next, so … no “herd mentality”, theoretically. We all can think of counter historical examples, of course.

    -arnaud
    Search is the OS!

  • http://www.cameronolthuis.com Cameron Olthuis

    Great article Arnaud!

    Re: Social search… Wouldn’t you say that the long tail is one the flaws of social search? If X number of queries are only searched 1-3 times then the crowd isn’t big enough for the wisdom on those results.

    In my opinion, Google(or Y & M) already has all the info they need for social search. We vote with our click-streams, time spent on pages, etc… G already has that info.

  • http://dmoz.org/profiles/chris2001.html chris2001

    “The principle of opinion Independence is critical. There cannot be influence or as Surowieki explains, “cascading” effect from one to the next, so … no “herd mentality”, theoretically.”

    Hm… then maybe we should stop trying to use the “wisdom of crowds” as base for earthly search applications – we´d end up with tools that need to be manned by angels, who have access to pure reason itself, ínstead of humans ;-)

    Typical characteristics of modern democracies, that are important for stabilizing them and preventing that herd instincts take over, are standards (e.g. human rights, constitutions and laws of specific states) and institutions (e.g. courts of law, schools that communicate standards to young citizens). Applying this to the development of “social search”…

    Standardization: Successful “social search” projects will usually meet growing challenges in form of poor quality contributions, abuse and spam, which enforce the creation of standards for their specific core task (e.g. tagging, digging, article- or review-writing). These standards, once established, can help a lot to keep herd behaviour under control.
    Beyond the limits of specific projects… the more colourful the social search scene becomes, the more important it will be that the community of net citizens and the various search market players develop shared standards. E.g. what are basic requirements for “quality content”? What are basic criteria for “spam”? Without a minimum agreement on questions like these, collecting user input, sharing data or creating mashups will get more and more difficult in the long run.

    Institutionalization: Specific initiatives (usually Open Content and Open Source projects) will be charged with tasks which are very important both for the community of net citizens as a whole and the search market, but at the same time require such tremendous human resources that the community can´t afford doing them three times. The best already existing examples are writing an encyclopedia and maintenance of a general web directory. If you have a closer look how Wikipedia and ODP are used today, they already play a role that reminds strongly of an institution: their data are used for science, to seed new applications, or as a correction factor or reference standard against which results of other projects and tools can be checked.

  • Mark

    “According to Jupiter, 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 were seeking.”

    Could you please give more information on the source for that? Thanks!

  • http://www.theratingsguy.com RatingsGuy

    Social Search is a means for consumers to avoid advertising, SEO placements, and congestion within search. People trust other people more than they do advertisers of all types.
    Secondly, it is basic human psychology for consumers to educate first (using search) and validate second (getting opinions). Social search helps consumers move through validation and on to decision making. Anyone who helps facilitate the validation process to determine; trust, value, and quality will help and enhance consumer decisions. Consumers are not blind to G,Y,& M’s advertising keyword bias, and will seek alternatives in a NY minute for the second phase of decision making. IMO G,Y & M fail the consumer in favor of being a better Yellow Book.

  • 2valhalla

    Arnaud,

    Great read. Is it possible that users/contributors will pull value out in other ways than simply getting paid by posting video on YouTube or searching? Maybe the value actually resides in relationship (both tangible and intangible value). For example, if you are using a social networking site like http://www.lyro.com you might get intangible value from making a new business relationship. Or, if you get an RFI/RFQ/RFP, you might actually recognize tangible ROI.

  • http://searchistheos.blogspot.com Arnaud fischer

    Cameron, thank you for the comments and feedback; fully appreciated. You are very right regarding the tail’s query distribution. Many queries actually have a frequency of 1 or don’t even show up in search logs from one month to the next. There are over 10 billion docs inventoried by the major crawlers out there and only about 700 or 800 million unique users worldwide.

    Social search is complementary, additive and augments traditional algorithmic search. Social search is not a substitute to traditional search … just making search as we’ve known it potentially significantly better.

    -arnaud

  • nickd

    I agree that there appears to be a fundamental contradiction in the claim that “The wisdom of crowds – so well articulated by James Surowiecki – is at the root of emerging information retrieval tools”.

    In Surowiecki’s book, the successful examples of the use of crowd wisdom require independence between the members of the crowd. The math that underpins this is Bayesian Search Theory (c.f. The Theory of Optimal Search, and/or the classic story of finding the lost nuclear sub Scorpion). Surowiecki in fact offers lots of examples of where crowd wisdom doesn’t work – most all of which involve biases due to lack of diversity of opinion or independence of the crowd members.

    However, social networking, community based recommendation engines, blogs, voting/ranking, etc. all seem to violate the key enabling principle (independence) that allows one to apply Bayesian Search Theory (aka wisdom of the crowds) to the judgments of the participating individuals.

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