Search engines like Google or Bing have made it much easier to find the content we’re looking for. On the other hand, because of its algorithm, they are becoming irrelevant for some type of information such as upcoming events. There is a huge opportunity to improve the search experience by leveraging social graph. Unlike the existing search engines, this new engine gives entire priority to the popularity among users in calculating the relevancy. The contents are not necessarily personal data but any type of digital data on the internet such as music, news, articles from the publishers and so on. Users consume these contents and evaluate them by putting comments, link in tweets, ratings, and tags or just “Like” it. Those users’activity will be the source in calculating the relevancy. In other words, it finds the right contents through the lens of collective intelligence. What’s more, users can optimize the result set by adjusting the engine. They can tune the collective intelligence to include only likeminded people or people in the same country etc. to get more relevant content.

    This engine is not going to replace the current search engines. It is suitable for the kind of contents that fluctuates with user sentiment such as large events like Olympic game or super bowl. It’s also suitable for the events happening now or don’t happen yet such as today’s baseball games, rumors about new songs and so on. By adjusting the collective intelligence to include only people in special area such as bikers, it becomes much easier to find the contents you’re looking for. As we go down this path, we’ll see innovative search experience that gives us not just reactive search results but more proactive suggestions in which we can stumble upon treasures out of trash.