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02.02.10 What Ranks Tweets In Google's Real Time Search?  By
Brian Solis In 2009, Google struck a deal with Twitter, rumored at $15 million, to integrate tweets into keyword related Google searches. And last month, Google also integrated real-time search technology to surface blog posts and news content as they hit the Web - dramatically improving the previous five to 15 minutes its spiders would take to crawl the Web. I should also note that Collecta also offers the ability to search the real-time Web, but its results also include popular networks within the social Web. Between Google and Collecta, Twitter Search is starting to show its age. The opportunities and benefits of accessing the real-time Web also represent its most notable deficiencies - the ability to truly focus the stream of cascading information into a river of relevance. Companies such as My6Sense are using a form of "digital intuition" to escalate tweets that match our patterns, behavior, and content we read. We are now staring in the face of a more sophisticated era of real-time search that will further advance, localize and personalize over time. And, everything starts with the experimentation of sophisticated algorithms that filter and rank the content we're hoping to discover. For example, Google recently adapted its PageRank technology for surfacing related tweets. PageRank was originally developed to help find relevant Web pages through traditional search and was Google's primary differentiation in a world of commodity search platforms. Essentially, Google's PageRank assesses the importance of Web pages tied to keywords based on link structure. Authority is determined by the quantity and quality of inbound links to each page as well as the branches of outlying link relationships that tie other pages to those within the first degree of inbound connections. In other words, the more links to a page and the more linkers to each link, the greater the value of the original page. The challenge with real-time search is tying tweets or other social content to notable producers and their networks of reputed followers and sub-follower architectures. In an interview with Technology Review, Amit Singhal, a Google Fellow who led development of real-time search, said "You earn reputation, and then you give reputation. If lots of people follow you, and then you follow someone-then even though this [new person] does not have lots of followers, his tweet is deemed valuable because his followers are themselves followed widely. As Singhal emphasized, "It is definitely, definitely more than a popularity contest." Google also examines the signal in the noise, to surface the most relevant tweets related to common as well as obscure subjects. And as Twitter itself advances the technology that packages tweets, such as geo-location data, we can expect to see a rapid evolution of real-time search. Basically, a follower is the equivalent of one page linking to another on the Web. Google recognizes each as a form of recommendation. So as higher quality pages link to sources, the original page increases in value. In the Social Web, reputed users who follow other users inherently increase the stature of the individual to whom they connect. Searching for a particular keyword now will produce qualified results for Web pages and also content published in Twitter and other social networks, ranked by the authority of the page and publisher of social objects as assessed by PageRank technology. Continue reading this article. About the Author: Brian Solis is principal at FutureWorks PR, an award-winning PR and Social Media agency founded in 1999. FW PR bridges the communications gap between companies and their customers, and between products and their specific benefits for their target markets. Solis blogs at PR2.0, http://www.briansolis.com, and regularly contributes to many industry trades. He is also frequently quoted in articles relating to technology trends and Marketing/PR strategies. |
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