Visual Discoveries Empower Superior Early Warning Intelligence

Several weeks ago I wrote about the evolution of Discovery intelligence from its foundations in Search intelligence.  Discovery is the Next Major Step of Awareness Beyond News Search.   At that time, I used this definition of discovery:

Discovery - the measured and prioritized alerting to targeted recipients of relevant "news" and trends pertaining to their intelligence interests. 

 

An important outcome of discovery is Early Warning alerting.  Business, political and financial decision makers are increasingly harnessing the swarm intelligence of news and social media to obtain early warnings about their interests.  In particular, early warning discovery covers these threat categories as they pertain to news and social media:

• Threats can be evolving "over the horizon," beyond the scope of daily or weekly awareness as part of new and unexpected connections.  These connections can be among hundreds of potential competitor-buyer-supplier relationships influenced by new technologies, governmental actions and societal trends.  Similar political connections can be evolving among politicians, voters, interest groups, and policy issues.
• Threats can be hidden in torrents of daily news and social media flows - visible if one were able to systematically find and prioritize the interesting trends and connections.

We use innovative visual and animated "radars" to enhance the scope and speed of the early warning discovery process.  The human ability to perceive warning imagery and patterns is 50,000 times faster than the reading of text about potential threats.  With this greater perception speed, decision makers can scan a larger scope of potential threats in less time than traditional early warning reporting.  Our early warning process converts huge volumes of news and social media into images and patterns that catch the eye of decision makers who use the visualized patterns to drill down to the specific news and social media articles.  No human can possibly rely on "search" in high-volume news and social media environments to achieve a viable early warning system.  Threats will be missed.  Visually assisted discovery processes are the modern solution for early warning.

 

News Radar Discoveries Are Most Interesting When a Market or Politial Storm is Brewing.

Weather radars are most interesting when storms are brewing and threatening patterns can be discovered and tracked. The same can be said about News Radars.

News Patterns algorithms have been tracking and plotting the patterns regarding US politics for several years. Approximately 15,000 articles and blogs have been tracked and patterned each week. Interesting patterns include the most relevant candidates and issues, as well as important connections among candidates, issues and voting groups. Radars change day by day as new news is collected and new patterns emerge.

On May 10th, 2013 the US Internal Revenue Service announced that some of its personnel were inappropriately targeting conservative political action groups, including the Tea Party.  Within a short number of days, this IRS announcement spawned a "storm" of news activity in the US Politics News Radar.  A cell of news activity and connections quickly emerged among the topics of Tea Party, IRS, Taxes and Conservative topics.  This political storm cell has been moving to greater relevancy, approaching the Obama topic.  Other topics like Immigration, the Economy and Gun Control are losing relavancy.

The IRS event also spawned a new political topic: Scandal.  The Scandal topic is also moving to greater connectivity toward the Obama topic at this time.  There is no doubt that the White House will be doing all in its power to dissipate this political storm, before it becomes any stronger or closer to the Obama news topic.
 

Discovery is the Next Major Step of Awareness Beyond News Search

We are now entering the era where discovery is the next major step of awareness beyond search in our information economy.  Discovery enables a superior competitive awareness within a very small window of user/client attention.  The "routine" search for news and social media is transcended by real-time and actionable discoveries for individual decision makers.

Search has been the natural first step in Internet awareness.  Information utilities created massive databases of news, blogs, social media and tweets that were indexed for ease and speed of searching via keyword queries.  Search is easy and direct, and as time progressed, analytics became enhanced summaries of pre-loaded search queries for public relations and media monitoring dashboards - not in order to support decision makers & discovery.

News search is self limiting for decision makers:

• Search could never enable surprises, as it presumes that the searcher already knows for what he/she is searching.
• Decision makers do not know the scope/definition of what their interest universe should be.
• PR and media monitoring, often the source for organizational news awareness, are not tasked to discover strategic competitive insights.
• PR and media monitoring are often barriers to keeping unfavorable & important information from decision makers.
• Superior competitive discoveries are found in a large universe of potentially interesting topics - too many for any one decision maker to track alone.

In a natural progression to solve the limitations of search, most Internet utilities are adopting discovery as part of their user value.   Google, Amazon, Facebook, Twitter, LinkedIN, Apple and QUALCOMM are recent examples of major efforts to deliver some form of discovery to users.  One definition of discovery is "unexpected" information not the result of specific searching.   My definition of discovery is this:

Discovery - the measured and prioritized alerting to targeted recipients of relevant "news" and trends pertaining to their intelligence interests. 

This definition also includes situations where recipients do not know their own interests or are not actively seeking information on those interests.  Some further clarifications are useful:

• news - traditional real-time news articles, blogs, videos, audio, social media and tweets
• trends - emerging or dissipating patterns that are relevant for competitive success
• relevant - having a significant and demonstrable bearing for the matter at hand. Merriam Webster Dictionary
• interests -  participation in advantage and responsibility. Merriam Webster Dictionary
• intelligence - information pertaining to survival or competitive response
• targeted - discovery based on individual identities
• prioritized - highlighting in descending order of urgency or relevancy
• measured - limited and in proportion to urgency and attention capacity of the receiver
• alerting - interrupting the attention of the receiver in the minimal time required for a message to be delivered

From the perspective of our Discovery Patterns (aka News Patterns), we are transcending what can be searched from hundreds of millions of expert and community content creators.  We are furthermore transcending the incredible machine content from news database that enable ever more powerful searches and analytics of those searches.  With our unique pattern seeking algorithms, we are enabling our free network members and our private clients to discover relevant news and trends for which they could not or would not be searching.  Discovery enables a superior competitive awareness (situational awareness) within a very small window (bandwidth) of user/client attention.

Content Will Always Be King Among News Creators

News Patterns has been a pioneer in the realm of discovery for over eight years. In my next blog I will give a detailed description of discovery versus search. This blog post will first set the stage defining the different types of news content creators.

Expert and Community Content are obvious to most information professionals.  Simply stated, Expert Content is created by authors and organizations whose business is to professionally inform target audiences either as subscriptions or advertising driven business models.  Community Content is the socially driven content that creators write or record as part of relationships with other community members.

Machine Content is often not considered, but nonetheless invaluable in the news content universe.  Machine content essentially synthesizes new content with algorithms and database processes out of original content from Experts and Communities.  Here are some examples of machine content:

• Search indices with built in relevancy  (made famous by Google and "page rank")
• Aggregation pioneered by LexisNexis and Factiva
• Low latency feeds that supply instant stock trading black boxes
• Media monitoring dash boards that track public relations interests
• News Patterns Discovery - algorithmic pattern seeking of trends or events of competitive interest  (More on this in next blog addition.)

The above venn diagram illustrates that there are many overlaps among the news content categories.  Here are some examples:

• Expert journalists often search machine Google as part of researching articles.
• Members of community Twitter often notify their followers of interesting expert articles.
• Public relations professionals use their machine media monitoring dashboards of expert and community content to research their next press release.
• Expert journalist use community Facebook as an alternative mode of article distribution.
• Community LinkedIN redistributes expert articles in an attempt to increase site page views
• etc.

I have several concluding thoughts:

• Expert and Community content could operate as viable, and independent categories.
• Machine Content is completely dependent on Expert and Community Content.
• Simple forms of machine content (as in better searches and monitoring analytics) can easily be adopted by expert and community content creators; whereas the reverse of expert or community content cannot be readily created by the machine content category.  Therefore for machine content creators to maintain their market viability, they must be increasingly innovative in the user value that they add to the "content is king" news universe.

Update: Risk Topics Under the Surface of Financial Meltdown Radar

Earlier this year (February 5th of 2013) I wrote that our news patterning process had discovered the threat topics of Capital Controls and Bank Runs. With the recent events in Europe - Cyprus more specifically - our financial meltdown radar continues to track the growing disruption of these two threatening topics to world financial stability.

The swarm intelligence of thousands of news content creators, as discovered by our news patterning algorithms, saw these threats coming long before Cyprus became a news headline.

Risk Topics Under the Surface of Financial Meltdown Radar

News Patterns has been creating News Radars for many years. A News Radar is an animated visual system for representing competitive patterns among market players. These market players can be competitors, suppliers, buyers, government actions, societal trends, etc. A very complex radar like Financial Meltdown can be composed of 30,000 news and blog articles per week.

Back in 2009, we were often asked if our radars saw interesting patterns that might have foretold of the pending financial meltdown initiated by unwise real estate lending. The short answer is no. We were not aiming our radars at financial markets at that time.

Now in 2013, we are aiming at our radars at world wide financial markets. We call this radar Financial Meltdown.

Beyond the obvious topics of Recession, Recovery, Debt, Deficits, Unemployment, etc, this radar is tracking some very interesting topics that will serve as an early warning of financial system risks:

• Bank runs
• Capital controls
• Nationalization
• Seizure of retirement accounts
• Hyper-inflation
• Hoarding
• Bartering
• Debt downgrading (especially US Treasuries... ouch!)
• Gold and precious metal prices/accumulation
• Transfer of sovereign gold from US depositories
• Commodity prices
• Rationing
• Austerity
• Unrest (rioting, protests, etc.)

These tracked topics will seldom be front page news or conversation topics in television talk shows.  Nevertheless, all of the above have emerged to some degree over the past year.  Seekers of financial risks now have a powerful tool in our Financial Meltdown radar to discover risk trends that might be lost in the "fog of news."

Candidate Romney Won the Battle but Lost the War for Presidential Election News Patterns

News Patterns has been tracking and patterning the news of the 2012 US presidential election for several years. Millions of articles were collected and subjected to our pattern discovery algorithms. A very powerful aspect of our news patterning is that patterns in the news often anticipate or closely correlate to actual voter behaviors. This past Tuesday, all the patterning came down to the actual voting. Here is what we saw and would have recommended to both Romney and Obama campaigns:

1) The 2012 News Radar correctly displayed that the election was about Obama versus Romney, showing both of these news topics as central and anchors in News Radar.

2) Romney campaign succeeded in making the logical topics of Economy and Jobs as central election topics. Nevertheless, the Obama campaign trumped this campaign battle success with its own news topics.

3) The Obama campaign was successful in creating the emotional "war on women" as a central campaign topic.

4) Super storm Sandy gave millions of voters an opportunity to see Obama as the leader in times of need and citizen support.  Governor Chris Christie made this a super topic by reinforcing bipartisan imagery with Obama just before the election.

5) Obama campaign gathered additional support with Education and Fix Washington topics.  Romney campaign contested the Fix Washington topic.

6) Romney used Spending as one of his campaign topics, yet Obama team muted this topic with associations of "do nothing Congress."

7) It was a great surprise to News Patterns analysis team that Romney campaign did not make better use of Fuel Cost and Food Cost topics, both of which were essentially irrelevant on election day.

8) The Health Care-Tax topic, created by the Supreme Court was also not used by the Romney campaign.

9) It is also surprising that Team Romney did not use Security/Arab Spring topics to their advantage.

If there was a meta pattern that points to the Obama success in the 2012 election is was this: the hard facts of Economy and Jobs as targeted by team Romney were trumped by US electorate wanting emotional comfort, including the idea that their choice from 2008 was a good man and leader.  To the undecided, still on the fence in the previous week, the imagery of Obama the leader in time of crisis over Hurricane Sandy swayed them in the direction of Obama.  There was no time for a Romney recovery.  The Romney campaign never built up a reservoir of emotional attraction to Romney the man and leader, nor an emotional distaste for Obama the man and leader.