News Patterns 2012 Radar Correlates With Alaska Polling Results for Likely Presidential Candidates

News Patterns has been operating an active intelligence network regarding possible Republican contenders for the 2012 US Presidential primary election. Every day thousands of news and blog articles are collected, filtered for noise, and searched for interesting connections and patterns. After billions of pattern matching calculations are completed, a News Radar is produced that represents connections and relationships among the news topics. In the case of the 2012 radar, the topics are potential 2012 contenders and the issues that may define them in a prospective campaign. As new news is collected and patterned, the News Radar moves and evolves to reflect the new data.

On August 28, 2010 the 2012 Presidential News Radar displayed that the top GOP contenders were Romney, Palin, Huckabee, Gingrich, Bush and Paul in this order. In the following image, one can see these top contenders clustered about the center of the 2012 News Radar. Additionally, the distance that a candidate is plotted from the radar center is typically inversely proportional to actual polling results. For example, in the displayed news radar as follows and in larger version here, the 2012 News Radar would indicate to us that Romney and Palin were the top contenders as measured by news patterning.

Also on August 27 and 28, 2010, a poll of Alaska voters was taken, probing likely preferences for 2012 GOP candidates. The results were published in Politico and are as follows: Romney 20%, Palin 17%, Huckabee 17%, Gingrich 16% and Paul 10%. The results did not state if other candidates like Jeb Bush were also included in the poll.

The thing to notice in comparing the News Patterns results with the Alaska poll results are that they are remarkably similar in the list of the names and the order of those names. The polling method started with a forced list of names that were used to question Alaska voters. The News Patterns method started with thousands of news and blog articles that calculated into a primary list of 2012 candidates with some sense of priority. This is a good example where News Patterns algorithms can approximate other methods (polling) of determining the collective beliefs of groups of people.

News Patterns Discovery 2: Searches Without You Needing to Type

In my previous blog, News Patterns Discovery - The Disciplined Enabling of Serendipity, I referenced a Wall Street Journal article. In this blog I will continue my reliance on the WSJ with an interview of Google CEO, Eric Schmidt. On Saturday (August 14, 2010) , the WSJ published this interview of CEO Eric Schmidt: Google and the Search for the Future conducted by Holman Jenkins. In the article, Schmidt had these things to say:

"...more and more searches are done on your behalf without you needing to type."

"I actually think most people don't want Google to answer their questions," he elaborates. "They want Google to tell them what they should be doing next.":

These are two ideas captured by our existing News Patterns innovations.  :

* Our patterning and radars suggest interesting market events that are discovered with powerful algorithms.  Then with a single click, a user can access the desired articles that are retrieved with complex search logic.  The end result is that simple clicking results in potentially interesting or surprising articles that were not typed in as searches.  We call this process Discovery. News Patterns implements this type of "searches without you needing to type" in visual News Radar interfaces and discovery briefing email.   :

* Our algorithms also suggest what our users should look at first or "should be doing next" by first discovering patterns, then prioritizing many possible patterns to investigate.:

Beyond that sophisticated algorithms that enable the above innovations, News Patterns and Google are relying on a useful context for their users. In the above WSJ interview, Eric Schmidt uses the example of real-time proximity enabled by GPS phones, that might tie a user's needs with near locations of products or services that can satisfy those needs. In the situation of News Patterns, the context that we create regards potential market or political threats driven by rivers of news signals. By seeking relationships among many different competing factors, then alerting users when relationships might be changing or new relationships are emerging, News Patterns draws users attention to information areas that might be interpreted as threats or opportunities - without typing search terms!:

The net result is a faster and more timely provision of useful information to News Patterns users without them even knowing that they should be seeking the particular news articles.

News Patterns Discovery - The Disciplined Enabling of Serendipity

On April 5, 2010 L. Gordon Crovits wrote this article in the Wall Street Journal: The Search for Serendipity. At the time that I read this article I was nodding in agreement with this particular passage in the article:

The challenge for modern information consumers becomes: How do you discover what you don't know you want to know?

Old-time print journalists bemoan the absence of serendipity—the accidental discovery of stories that readers didn't know they were interested in reading. In the words of a recent blog post at the Nieman Journalism's Lab site, "While there is more news on the web, our perspectives on the news are narrower because we only browse the sites we already agree with, or know we already like, or care about." With newspapers, by contrast, readers discover "things we didn't care about, or didn't agree with, in the physical act of turning the page."

Part of the reason that we browse that which we are comfortable is because we as humans have a very low input bandwidth when measuring the amount of information that we can input to our conscious minds by reading. In fact this reading input rate is in the range of 200 bits per second. Consider this 200 bits per second as glacially slow when considering that our minds input graphical information at the rate of 10,000,000 bits per second. There is little wonder why we soon fatigue when exposed to the huge volumes of text news information that are at the other ends of search queries and alerts. By returning to sites that we agree with, as stated by Nieman Journalism lab, we are actually employing a strategy of using scarce information input bandwidth. It takes far less energy to read something with which we agree, than information that challenges our beliefs.

In our News Patterns world, we enable greater serendipity by converting large volumes of news information into graphical patterns. It is the visual pattern that incites the interest of our users. By intention, some patterns look threatening, new, and unexpected. Once a pattern has earned the attention of our users, he/she can easily drill beneath the surface to the actual news articles defining the graphical pattern. Like scanning a news paper, News Patterns users scan large volumes of news data, quickly bypassing some information while focusing on others, all without a forced reading of too many individual article details.

With such a graphical scanning process supported by algorithmic patterning processes that discover patterns of probable interest to our users, we empower them to a superior situational awareness of the here and now, and enable them to transcend comfortable sources with discovery or serendipity.

 

Its All About the Billions of Computations, Patterning Algorithms and Alerting in News Patterns

Here is an interesting anecdote about the use of News Patterns as a market analysis and discovery tool. 

Each day, we collect 10,000 articles related to Wireless industry as part of our "sector chief" assist to our clients.  This figure does not even include social media inputs.  Obviously, one cannot read or even scan them all.  Nevertheless, the goal is to find trends or discover new combinations among competitors, customers, technologies, resources, regulations, etc.

In Wireless Application radar, we noticed a new combination that was outlined in yellow, signifying that the connection was new and not seen in recent history.  Using a 1 to 1 permutation calculation, there was a 1 in 800 chance that we would have attempted to make that specific connection, even if we had the patience to create the specific AND logic to search the combination.  (The 800 figure is derived from a starting point of 40 open folders/topics using the equation of n!/(2(n-2)!)

Upon clicking on the highlighted yellow connecting line between Windows Mobile (software) and HTC (handset manufacturer), our news analysis system surfaced a rumor that handset manufacturer HTC might be coming out with a Windows phone as rumored in the UK.  This market scenario was interesting to our team and will be tracked for further news patterns developments.

Its about the billions of computations, patterning algorithms and alerting in News Patterns that we could go from 10,000 articles and 800 combinations to an interesting discovery in seconds.

Useful Context Is the Future of Human Information

In a recent article, Nokia: 'Say goodbye to the apps phone... Nokia's EVP of services Tero Ojanpera stated that "We are moving to a place where your mobile device will be able to offer a limitless amount of context and personalisation in real-time,"

I completely agree that useful context is the future of user information. Think about it. In ancient societies, people's lives were lived in useful context. In the villages where they lived, information about the weather, crops, hunting, family, health, leadership, conflicts, history, and societal relationships were basically ever-present. A human did not need to look far to find needed information or context. Useful context was always present or easily accessible with the human powers or sight, taste and sound.

Now roll the clock forward to our time. Our digital world has enabled us to be aware of events across the globe, way beyond our normal human capabilities of natural perception. We can choose the communities to which we belong, only connected by an Internet connection. With a click of a button, we can become overwhelmed with information that is not connected to our context.

In our development of News Patterns, we enable our users to create a useful context, that serves as a lens through which they can collect and interpret news that might be relevant to themselves. No single News Radar attempts to be definitive on each news fact. Rather, News Radars create the environment that increases the probability that useful trends will be perceived and investigated further. In a sense, News Patterns is creating a continuous environment where a user can continually perceive his/her market or political space in a useful context, just as villages of old provided context for early human civilizations.

The crazy genius who has newspaper and magazine clippings pasted all over their walls

In Mike Melanson's recent article in ReadWriteWeb, he made a reference to "the crazy genius who has newspaper and magazine clippings pasted all over their walls with circles and lines and highlighted paragraphs to find the hidden common threads and secretly wished that you were crazy and smart enough to be that guy?" Of course one of the best references to this is "A Beautiful Mind," the 2001 movie about the mathematics genius, John Forbes Nash. In the movie, there were many scenes where Nash, played by Russel Crowe, surrounds himself with news clips that he attempts to connect as patterns. When I saw the movie then, I related to Nash's attempt to create a visual representation of connecting ideas. I also related to the idea that such methods might seem crazy.

But I did not think that visualizing these was crazy. In fact, my first degree and job were in structural engineering. You know, the engineers that build bridges and sky scrappers. We could not do our jobs as engineers without CAD, which is a visualization system supported by underlying calculations. So in many ways, the foundation of News Patterns is the goal to visualize patterns in markets, society, politics, and finance based on first finding patterns in the news, then creating visualizations that convey these patterns to users. With the flood of news, blogs and social media, I cannot imagine distilling understanding from so many articles without News Patterns engines.

Free versions of News Patterns access

We have recently been asked about free versions of News Patterns access. This we can do, and eventually will. If you have suggested features for this application, please add comments to this posting. Nevertheless, the News Radars on our site are a good starting point for real time intelligence and discovery.

The cobbler's children go without shoes

This is my first blog entry, even though you would expect the   president of a news and social medial intelligence company to be well   versed, himself in social networking communication.  Now I will start.    Just last Thursday afternoon, I was interviewed by Mike    Melanson of ReadWriteWeb.  Before we knew it, his article was on   line, it resonated with many of his readers, our servers were smoking   with activity, and the social media was buzzing about our innovations   with visualizations of news.  Mike and ReadWriteWeb are indeed   influential.

Here is his article: News Patterns: Finding Hidden Threads in Everyday News. Nice job Mike!