The Human Algorithm: How Google Ranks
Tweets in Real-Time Search
By Brian Solis, blogger at BrianSolis.com and principal of FutureWorks, Author of the new book
Engage!, Co-Author, Putting the Public Back in Public Relations and Now Is Gone
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.
(cc) Brian Solis, www.briansolis.com - Twitter, @briansolis
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
(cc) Brian Solis, www.briansolis.com - Twitter, @briansolis
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.
In the eyes of Google, the adaptation of PageRank for Social Media essentially
creates a human algorithm or a PeopleRank of sorts that may eventually serve as
a foundation for also assessing the authority of an individual in the social Web.
Other companies are also introducing new services to measure general authority
for individuals online. Klout, for example, developed a sophisticated platform for
measuring the influence of users in Twitter. Based on three sophisticated stages
of semantic calculation (True Reach, Amplification Probability, Network Value)
Klout can determine not only the level of influence of any user on Twitter but also
the most influential voices tied to topics or keywords. Microsoft’s search engine,
Bing, is also including tweets in its real-time search feed and could, for instance,
integrate Klout’s influence engine to rank tweets and other social objects to
qualify results.
But while the idea of ranking influence on the social web is interesting and
necessary, it is far from perfected. Running searches in either engine today will
only reinforce this sentiment. However, with that said, it is helping us by
reducing the obstacles that typically prevent or prolong the process of finding
pertinent information. It will only improve over time regardless of our personal
views on establishing a hierarchy of people in social media.
(cc) Brian Solis, www.briansolis.com - Twitter, @briansolis
As the human algorithm continues to evolve, it transforms the definition of and
logic for relationships. We’re adapting how we connect to one another and also
constructing new roads for sharing, filtering, and ranking relevant social objects.
The ties that bind us now serve as the source of how we discover information and
also how it finds us. And as such, the relationships we maintain on the Social
Web determine the ranking of the content we produce and its place within the
social hierarchy of search results.
Perhaps the next iterations of Search Engine Optimization (SEO) and Social
Media Optimization (SMO) will focus on enhancing the link structures of human
relationships to escalate the prominence of our stature and the social objects we
create and share.
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Brian Solis is globally recognized as one of most prominent thought leaders and
published authors in new media. A digital analyst, sociologist, and futurist, Solis has
influenced the effects of emerging media on the convergence of marketing,
communications, and publishing. He is principal of FutureWorks, an award-winning New
Media agency in Silicon Valley, and has led interactive and social programs for Fortune
500 companies, notable celebrities, and Web 2.0 startups. BrianSolis.com is ranked
among the top of world's leading business and marketing online resources.
Solis is the author of Engage! The complete guide for businesses to build, cultivate and
measure success in the new Web.
In 2009, Brian Solis, along with Deirdre Breakenridge, released, Putting the Public back
in Public Relations.
Connect with Brian Solis on Twitter, LinkedIn, Tumblr, Google Buzz, Facebook
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