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Internet Futurism: Social Search

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The second half of our Internet Futurism series will focus on the emerging technology of “Social Search.” Social search is the most significant change in the landscape of search since Google introduced the first generation of Page Rank more than a decade ago. Google won their dominance by creating an algorithmic search ranking system, and now they are reintroducing the human factor.

So what is social search? And why is it going to be so important?

Let’s step back a moment.

Perhaps one of the most unexpected social developments following the widespread adoption of the Internet was the immediate gravitation towards micro-communities. Many people envisioned the Internet as the ultimate unifier. They predicted that it would unite the whole world into a single, global community: erasing borders, and breaking down notions of censorship and national identity. Instead, something very different happened. Yes, geographical boundaries were broken, but this did not lead to a single world-wide community. Instead, micro-communities emerged organized purely around common interest, instead of being based on the happenstance of geography.

These micro-communities reflect some striking similarities to small agrarian communities, artist colonies, or Utopian communes, however in many ways they represent something very “new.” This has social consequences both positive and negative. In these communities people can essentially pick and choose their neighbors. This provides a tremendous unity of interest and purpose, but reduces exposure to conflicting ideas, and polarizes and alienates other points of view.

So what the heck does that have to do with search results?

10 years ago, the game in search results was to provide the best universal rankings for content no matter what the user’s interest or location. If the search query was about snowmobiles, it was Google’s job to find the very best website on snowmobiles in the world, and make that the first result for everyone.

But recently, the search engine companies have gotten wise to the notion of community. About five years ago, this was reflected in a shift to delivering search results tailored to your physical location. Now Google’s job was to find the best website about snowmobiles in California and make that the number one result for Californians.

But as we’ve seen above, this notion of community based on physical location is outmoded on the web. It doesn’t stand up in these communities of “chosen neighbors.” Now search engines are realizing that the real prize is is in these communities. Now it’s Google’s job to connect the Vintage Snowmobile-ers’ Community with vintage snowmobiling websites, to connect vacation and ski resort lovers to more casual snowmobile rental websites, to connect younger communities to snowmobile video games, etc. To each community according to their need and interest.

Instead of providing the best universal rankings, a search engine now has to provide the best community rankings.

How are search engines accomplishing this?

The problem with trying to provide community-oriented search results is that most scenarios aren’t quite as straightforward as the “snowmobile lovers” examples outlined above. The most common kinds of communities aren’t neatly organized around a single interest (e.g., snowmobile lovers), but rely on complex interactions of interest and individual/demographic differences (e.g., teenage vintage snowmobile lovers from California).

The other problem is that is that every individual has cultivated their own unique portfolio of communities overlapping with those of their friends. It’s very rare for one person’s list of Facebook friends to be exactly the same as someone else’s. There will be a large amount of overlap, but even when friends and common interests overlap 90%, the remaining 10% difference between 2 individuals reflects membership in completely different communities.

Search engines are having a very difficult time targeting results to these nebulous communities algorithmically. Instead, they are resorting to re-injecting human influence into search results, and going about it in a few different ways.

1 – Direct influence: under a direct influence model of social search, members of one’s community can directly affect the search results that will be presented to other members of that community. Google’s +1 search results system can be considered a direct influence method.

2 – Secondary influence: a secondary influence model does not involve community members deliberately “voting up” certain search results. Instead it looks for “buzz.” Are some results being tweeted by members of a certain community? Did this link get passed around among your Facebook friends? If the search engines see this kind of activity they can use this as the basis for adjusting the search results for these communities.

Until very recently, Google only operated on a partial, secondary influence model. They looked for “hot topics” on social networking services, and bumped their results. But these were still largely universal ranking changes, not targeted specifically at the communities that produced this buzz in the first place. Indeed, Google had little relevance in these arenas, because the source of these ranking changes came from within these existing communities. People were already finding these links through shared Facebook posts…not through Google searches. Google was following, rather than anticipating, trends.

In response, Google tried to implement a method of direct influence. With Google +1(not to be confused with Google+, which we’ll discuss shortly), any user who found a search result they like can vote it up, so that their friends would see it in a higher position if they were searching for something similar. However, the adoption rate on this was poor, and it required that Google users organize themselves into communities, which at the time, they had little motivation to do…

…until Google+ came out.
As Google’s direct competitor to Facebook, Google+ integrates both their direct and secondary influence models of social search, within a social network that users will happily participate in. The concept of “Circles” (Google+’s version of Friend groups) is an explicit realization of this idea: a portfolio of communities. Users are now organizing themselves into these community groups within Google’s system, anything they share can now be realized in direct influence, rather than just secondary influence on the results of their fellow community members. It’s going to be a very different landscape.

It’s a very exciting time. More and more the Internet is being designed to “know” what you want, and to predict what you’ll be looking for. This could be an incredible tool for strengthening these micro-communities, but they’ll only make these communities more insular. Furthermore, the overarching privacy concerns that this raises are not insignificant, and should not be taken lightly.

What does all of this mean to you, the small business owner?

Increasingly, the web is becoming community driven. Participation in these communities is no longer something extra that a business owner can do. Very soon, it will be absolutely necessary.

Tim L – CoachingWebsites Support
Email any questions to [email protected]


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