Facebook's Potential Search Power Will Not Surpass Google's

On April 22, 2012, Diane Mermigas wrote this article in Business Insider: Facebook's Potential Search Power Could Surpass Google's.  The gist of the article is that the rich human interaction within Facebook is a superior method of creating invaluable context about Facebook members and their friends, thereby enabling a superior matching of advertising content and search results with individual Facebook members.  This could very well be true - to a point.  And that point is the line where sharing and updates crosses over to become spam for the notified Facebook members.  It is my observation that younger Facebook users and some demographic groups have higher tolerances for sharing based on extended periods of time for Facebook application usage.

But my analysis here pertains to professionals in business, finance, politics and societal security.  While all of these types of people may have Facebook identities, it is highly improbable that they are substantially sharing, liking, or friending within the external communities where they compete and earn their livings.  Sure, there are exceptions like Realtors and insurance agents where selling is dependent on personal relationships.  Yet few in competitive environments are willing to reveal context about themselves that could expose personal weaknesses.  Few were also willing to offer any reason for a potential customer or voter to choose a competitor. 

Over ten years ago, we envisioned a news intelligence system that was augmented by collaborative insights.  We called this collaborative insight our "swarm index," named after the swarm intelligence found in colonies of bees.  Our swarm index enabled commenting, sharing, and changing of news article urgencies.  We also implemented powerful versions of "liking" that included measures of group threats or opportunities, far before Facebook.  In spite of all these community capabilities, it did not take us long to realize the true needs and behaviors of professionals in private networks to whom we targeted our news intelligence networks:

• Our network members dedicated minimal time to collaboration or sharing.  They were just too busy to add more work to their daily schedules.
• Our network members were concerned that if they were perceived to be uber collaborators, then they might correspondingly be perceived to have too much time on their hands.
• People were concerned to offer collaboration content that might appear trite or untimely to their organization peers - and even worse to offer opinions that were contrary to shared organization beliefs.

All of these issues were solvable.  Our solutions rested on the foundations of low member collaboration expectations and smarter context algorithms - the general approach of Google. 

Looking ahead, it is understandable that Google is seeking more dedicated collaborative or community inputs that will help improve the context of its searching and advertising.  And it is expected that Facebook will continue to leverage its community contributed content and context.  Nevertheless, not all Internet users are potential Facebook content editors.  Many professionals (as in the 150,000,000 Linkedin members) will continue to rely in the intelligence of Google, and not risk the downsides of self contributed Facebook content.

World Financial Meltdown Threat Patterns #1: An Unhealthy Calm

Just after the US financial crisis in the latter part of 2008, I was having dinner with a friend who had lost major parts of his retirement savings. He was not your expert investor. Rather he was a smart professional who trusted the advice of his financial advisor. It was obvious that his advisor did not see the coming storm in mortgage backed securities and the deleterious effect that this storm would have on the entire financial market. My friend was trusting what supposed experts were seeing.  At that dinner, I asked myself the question: "Why not enable ordinary people to see more of what is important around themselves - especially significant risks?"

Like 2008, significant risks are brewing in world financial markets.  The following News Radar is a pattern discovery and tracking system based on tens of  thousands of daily worldwide news and blog articles.  In particular, the patterns that it seeks are patterns that portend potential threats or opportunities in world financial markets.  Over the past five or more years, we have discovered that seemingly chaotic and overwhelming flows of news contain a collective intelligence from thousands of news content creators.  These news makers, both professional and novice, tend to write about what is important or interesting to themselves.  When we add all their ideas together, an overarching intelligence, or swarm intelligence, can appear.

This World Financial Meltdown Watch Radar was plotted on April 18, 2012, and it contains over 160,000 news and blog articles from the previous four weeks.  One can see an active version of this radar at http://www.newspatterns.com/show_radar.php?name=financial2.  (Note that radar changes day by day with new news signals, and your browser will need to be compatible with HTML 5 to see this animation.)

The simple explanation of this radar is that the most relevant ecosystem topics are drawn to the center of the radar space.  In this case, the radar center is occupied by Spain and Government Debt (center left) and Recession-Recovery (center right.)  Today, this radar is reflecting the market anxiety about the recent Spanish government debt offering as well as the uncertainty whether the world is heading toward recovery or recession.

There are many other interesting patterns to dissect, yet I would like to get back to my "Unhealthy Calm" threat pattern.  It is my hypothesis that world financial markets cannot get back to viability until governments start to significantly curtail pension and entitlement benefits for their citizens.  Governments cannot continue to live beyond their means.  Higher taxes are not the solution.  Super robust economic growth is also unrealistic.

If governments do start down the path of entitlement and pension reductions (also known as austerity) then I expect that there will be significant unrest in effected populations.  Think of Greece, Spain and Madison, Wisconsin.  The above News Radar will reflect this pattern with a coupling of the Austerity topic with Unrest, which will further display as a movement of both topics toward the center of the radar.

The fact that there is so little implementation of austerity by world governments, tells me that world leaders are "kicking the can down the road", and not really addressing the heart of what ails world financial markets.  Ironically, massive societal unrest will be a healthy indicator that world governments are addressing their debt problems.

This calm of needed solutions is a significant threat that more need to see and track.  The longer that Austerity and Unrest remain as peripheral topics in the financial radar, the more world financial risks will grow.

 

Looking at Context in the Context of News Patterns

We here at News Patterns often think about context as we develop our patterning algorithms and interfaces. According to the Merriam Webster definition...

Context: the interrelated conditions in which something exists or occurs; environment or setting.

We extend the definition of context to include relevant relationships that enable one to see things differently as a result of those visible or conscious relationships. This graphic illustrates the point about the power of context:

  

As one might suspect, both gray squares are actually the same color and lightness. Nevertheless, the gray square surrounded by black squares (left) appears to be darker than the gray square surrounded by white squares (right).  This visual perception shift is a result of the way our brains perceive patterns in light and dark fields.  We interpret the gray squares differently because of the the different contexts where they appear.

This same shifts in perception occurs when we are exposed to news signals based on these examples of news context from traditional news sources:

• The credibility of the news article source (history of relevant coverage and factual accuracy)
• The historical sentiment of the source (as in friend, foe or credible objective)
• The relevancy of the news as it pertains to current needed information
• The frequency of new story repetitions among different news sources

With our news patterning algorithms and animations, we extend the boundaries of context with these attributes:

• Thousands of potential relevant sources
• Extended periods of time (days, weeks, months and years)
• Topics that should be tracked as part of important interests
• News that correlates with archetypical patterns of competition
•  New topics that are deserving of active tracking
• Visual animations of context and trends
• Tracking layers set to anticipate actual market, political or societal events
• Trusted group memberships that share news and relevancies of news articles

Since all this extra context would produce an overload of text if it were all in written form, News Patterns uses image and animation layers to add context to relevent news for our network members.  Context in image form is interpreted by humans at amazing speeds.  The end result is greater insight (as in more useful context) in a shorter period of time.

I will add more on this topic in a future post.  See also my most recent  post: Animation Innovations for News Patterns Radar Interfaces )

Animation Innovations for News Patterns Radar Interfaces

In early February of this year, we added new animation layers to our News Radar interfaces. These animations were written in HTML5 so that they could be displayed across the widest range of Internet devices. We had three primary objectives:
* Connect the narrative of "swarm intelligence" with our radar visualizations
* Use movement to guide users to the most potentially relevant news and patterns
* Continue our progression to a video game like interface

The following image is a snap-shot of one of our animated News Radars.  Because this is a static blog page, movements are not active. Nevertheless, an active version of this News Radar can be seen at this location: Example Animated News Radar: Tablet Ecosystem



Since each News Radar can represent thousands of news articles, the addition of moving objects captures the feeling that the radar is composed of many of these articles. The nature of the movements draws attention to highly relevant competitive topics and important connections among topics. As the volume and intensity of object movements increase, so too does the probability that these topics and connections deserve more attention.

And once desired attention is focused on these movements, News Pattern members/clients can "play" the interface with instantaneous drill-downs to the actual news and social media that might be most relevant for reading. This ability to play the news interface enables an extremely fast process for gaining high level overviews of a competitive environment while focusing on the most relevant news.