Posts Tagged 'social networks'

Connection Strength & Context in Social Networks

This post continues the theme begun in the last post about the nature of networked intelligence, and the role of connection strengths and context.  This one reveals more of the theory that has inspired the “Trusted Sharing” app now being tested by a few friends and colleagues.


Networks are nature’s best embodiments of collective intelligence.

Networks are intelligent and adaptive, which means that they grow in intelligence as they adapt to events to fulfill needs.

The networks that are most important to us are:

  • Networks of living organisms, plants and animals that feed and protect us;
  • Networks of cells that make up our immune systems;
  • Networks of neurons that make up our brains;
  • Personal and social networks that make up our friendship and support networks, and health, transportation, economic, learning, and communication networks.

Our technology is now more than ever creating, using, and maintaining networks.

All networks are basically made of nodes and connections.   The intelligence of the nodes is important, but the real intelligence of networks is in the connections.

There are two super-attributes of connections that are especially important in all types of networks:  Connection Strength and Context.  

In order for a social network application to be most intelligent and useful it has to recognize, ‘understand’ and make use of these two attributes of connections – strength and context.

Current generations of social networks, like Facebook, LinkedIn, Twitter, and now Google+, are just now, and barely, beginning to recognize and make use of the strength and context of connections.   “Just beginning” means that there is much more valuable evolution that has yet to take place.

All people of course pay close attention to the subtle nuances of their network connections.   But it is definitely a challenge to design a computer-augmented social network application that can more fully ‘understand’ and make use of these nuances, which include the strength and context of connections.

To be successful, social network applications have to miraculously turn complexities and fine distinctions into features that are easy and intuitive to use, useful, and, most of all, that don’t get in the way.

Strength and Context of Connections

Here are some of the distinctions that exist in our ‘real-world’ understanding of social network connections and behaviors.

Context of connection is about what is shared.

Networks form within and around what people share:

  • Friendship, love, family ties (and hostility, aversions, common enemies)
  • Group and organization membership – based on commonalities such as shared interest, perspectives, goals, employer, profession or industry.
  • Exchange-driven contexts – e.g., buyer-seller, client-consultant, teacher-student.

More abstractly what we share are:

–   Interests
–   Values
–    Goals
–    Exchanges and collaborations

Strength:  How strong is the connection?

People easily understand that their connections vary in strength.   We intuitively measure strength in terms of how much the connection is:

–   Close
–   Trusted
–   Valuable
–   High in priority (for response or action)

Reciprocity

There is another important attribute of connections that is important to understand and make use of:  Reciprocity – also known as mutuality.

In social network theory reciprocity is understood in terms of the “direction” of the connections between two nodes:  A connection can extend from A to B, or from B to A, or it can be bi-directional, i.e., reciprocal.

If two people share the same interest (or goal or set of values or group membership) but don’t know each other, then they are each connected by the same context, e.g. interest (or goal or set of values or group membership), but they are not personally connected.

Yet even if not connected personally, they have a mutual connection to the same context; and that mutual connection can be an important incentive for reciprocity:  sharing information and ideas, responding to news & requests, providing help when needed, etc.

It is also possible that even if two people share the same context and don’t know each other personally, one person can “follow” the content that the other person makes available, in a tweet, blog post, article, book, video, etc.

This type of non-reciprocal relationship is Twitter’s sweet spot.  In Twitter if you follow someone’s posts they don’t have to follow you for the system to work.  And yet, following someone is often a way that a reciprocal relationship can start – by following someone back, or even by actually reading and commenting on what the other person posts, or by starting a direct conversation.

Trusted Sharing’s Approach

Trusted Sharing’s first public release will focus on developing a core layer for automatically determining and using both strength and context of connections to sort and filter incoming feeds and to target outgoing messages and feeds.  We already have much of that core functionality completed for use of strength of connections — enough to begin testing and refining with a limited number of test users.  The public release, when complete, will also include simple but useful methods for filtering and tagging content by topic (context).   However, automatically tagging and matching user-generated content by topic isn’t our focus for this first version.   Our preference is to partner with other developers who are already well down the road with automated topic recognition in socially-shared content.

If you would like to be notified when the Trusted Sharing beta is ready, leave a comment here, or contact me at dwork-trsh@spamarrest.com.

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Collective Intelligence in Neural Networks and Social Networks

Context for this post:  I’m currently working on a social network application that demonstrates the value of connection strength and context for making networks more useful and intelligent.   Connection strength and context are currently only rudimentarily and mushily implemented in social network apps. This post describes some of the underlying theory for why connection strength and context are key to next generation social network applications.

A recent study of how behavioral decisions are made in the brain makes it clear how important strengths of connections are to the intelligence of networks.

“Scientists at the University of Rochester, Washington University in St. Louis, and Baylor College of Medicine have unraveled how the brain manages to process the complex, rapidly changing, and often conflicting sensory signals to make sense of our world.

“The answer lies in a simple computation performed by single nerve cells: a weighted average. Neurons have to apply the correct weights to each sensory cue, and the authors reveal how this is done.” …

“The study demonstrates that the low-level computations performed by single neurons in the brain, when repeated by millions of neurons performing similar computations, accounts for the brain’s complex ability to know which sensory signals to weight as more important. ‘Thus, the brain essentially can break down a seemingly high-level behavioral task into a set of much simpler operations performed simultaneously by many neurons.’”

(The fact that neurons in the brain make a weighted average of thousands of inputs has long been understood in theory.  This particular study has surfaced much clearer evidence for exactly how the whole process works.)

Obviously individual humans are enormously more complex than individual neurons.

However, the way individual and collective decisions are made – i.e., decisions about what information is reliable and what actions to take – seems very similar in populations of neurons and populations of humans:

Each individual (whether neuron or human) makes a particular decision by making a weighted average of all of the inputs the individual receives that are relevant to the decision.   And likewise, the population makes its own particular decision by making a weighted average (e.g., taking a vote) of the decisions made by all the individuals in the population whose decisions matter.

In the case of individual humans, inputs relevant to particular decisions consist of opinions gathered from all types of media, including the publications and media channels they trust most, and the opinions of their trusted friends and other contacts gathered from direct interaction and social media.

However, individuals obviously don’t give equal weight to all of their sources.  Instead they give stronger or weaker weights to their different sources, including both positive and negative weights.

These weights also vary depending on context – that is, different sources are especially important for forming, reinforcing, or changing opinions, decisions, and behaviors related to politics, health, education, career and work, economic and financial choices, etc.

The implications that are most important are these:

1.  Understanding and using strength and context of connections is extremely important for enhancing the effectiveness of social network applications and other applications that are intended to improve individual and collective decision-making.

2.  If a population (community, nation, etc.) needs to make a critical decision, then it is essential to have all relevant perspectives fairly represented and fairly taken into account.  (Shooting your opponent, or censoring their ideas, or flooding the media with intentional misinformation and ridicule are not fair methods.)

3.  The perspectives and decisions of individuals are in fact extremely necessary to insure that the population as a whole makes the best possible decisions.

4.  Finding ways to reduce social fragmentation is essential for making both individuals and whole populations more intelligent.   Contributors to social fragmentation include:  Filter-bubbles, echo chambers, knee-jerk bias, narrow interests that take precedence over the good of all, and intentional manipulation by a powerful few of lower-level emotional reflexes (“knee-jerk biases”) among the many.  All of these kinds of influences tend to make both individuals and whole populations much less intelligent than they need to be for the whole group to thrive.

Social network applications that fully make use of the connection strength and context can help address each of these issues.  But of course, they also have to be easy to use, relevant, and compelling.

Good list of 2010 predictions for social media

Oct 27 post by Jennifer Leggio (ZDNet):

2010 Predictions: Will social media reach ubiquity?

The predictions are from 31 people in Jennifer Leggio’s personal network.   It’s a great collection, and valuable to read through all of them together.   A lot focus on use of social media for marketing, PR, and enterprise collaboration (a lot of the predictors are engaged in consulting or software for those areas).

Common themes:  Social media will indeed be ubiquitous; will spread more in the enterprise; will need more privacy controls (or not); will have more location-based apps; will require more filtering.

Here are a few excerpts that especially interest me:

Caroline Dangson, IDC@carolinedangson

“IDC survey data shows more than 50% of worldwide workers are leveraging the free, public social media sites like LinkedIn, Twitter and Facebook for business today. IDC believes the primary reason workers are using the consumer social media platforms is because their organization is not providing these types of tools itself”

(I believe there are other very good reasons for continued use of consumer social media platforms in organizations.  E.g., it’s hard to replicate the value of a global platform with 50+ million members .)

Peter Shankman, Help A Reporter Out@skydiver

“We’ll update to let people know where we are and where we’ll be. And the best part is, we won’t have to. 2010 will be the start of the time where our devices do it for us. FourSquare will auto-update our location via GPS, which will tell Twitter, who will add the #fb tag and notify Facebook”

“we’ll start to accept the concept that hey – maybe we really DO only need one social network ,which will bring us to 2011 – the year of the consolidation.”

Brian Sibley, Sibley PR@bsibley

“Domino’s experience taught us that when it comes to social media, you can’t just switch it on, like you can a traditional marketing tool. You have to invest the time to build a strong following in order to be able to use it as an arrow in your crisis communications quiver when the time comes”

Brian Solis, FutureWorks@briansolis

“2010 will be the year that we save us from ourselves in social  media…we will stop drinking from the proverbial fire hose and we will lean on filtering and curation to productively guide our experiences and  production and consumption behavior and interaction within each network.”

I’m looking forward to reading 2010 predictions from others.  Thoughts?

What do Meta Networks Need?

(Continued from Basic Case for Meta Networks and Global Transformation)

Meta Networks are:

  • Decentralized networks of people, organizations and networks,
  • Bound together by shared goals, values, and experiences.

Meta networks are crucial for fixing global problems before they overwhelm us.

Meta networks need passionate, committed, and talented people, plus ideas, funding, and other resources.   But they also need methods and tools to make the individuals, organizations, and network as a whole more intelligent and effective.

Here are four types of methods and tools that meta networks need:

1.  Connecting people and organizations.

a.  Connecting people to people and organizations to obtain:

– Ideas, expertise and help (employees, partners, consultants, advisors, volunteers)

– Funding (investors, grants, donors)

– Inside Intelligence & Influence (related to potential customers, partners, investors, employees, and suppliers, and agencies, policy makers, communities, etc.)

Examples of tools:
Job, volunteer and consultant matching sites and databases; professional social network platforms for finding needed expertise and affiliations and obtaining trusted recommendations and referrals (e.g., LinkedIn).

Examples of methods:
Network weaving and social network analysis.

b. Connecting people to content
(to obtain news, ideas, opinions, research, experiences, knowledge)

Examples – Generic and specialized Internet search engines, content management and knowledge sharing applications and portals.

2. Sources for Reputation, Fact-checking, Due-Diligence.
(Supports other needs, e.g., connecting people, decision-making, etc.)

Examples:  Generic Internet search engines; professional social network platforms for checking professional experience and getting personally trusted insights and recommendations; reputation sites (most are not very mature yet).

3. Messaging campaigns to spread awareness and actions
(e.g., awareness and actions related to voting, contacting policy makers, talking to neighbors, donating, buying or boycotting)

Examples:  Social media sites and tools (Facebook, Twitter, messaging tools, etc.)

4. Collective Thinking and Action (big category!)

a)  Removing barriers to communication and collaboration.
(Dialogue, listening, finding common ground, consensus-building, conflict transformation, use of stories, symbols and rituals, collective consciousness effects)

b) Identifying, understanding and solving problems
(Collecting facts and perspectives from all relevant sources; Innovating (exploring/scanning/brainstorming); Integrating perspectives to reach consensus/decision on best strategies and tactics; Prediction; Deliberation and planning (evaluating ideas from different perspectives, consensus building); and Getting commitments for action.)

c) Collaborative Action – requiring complex coordination of actions by many people and organizations.

Examples of a, b, & c:   Online and in-person methods and tools for dialogue, deliberation, and collaboration.   For a partial list see NCDD’s Framework for Dialogue and Deliberation.

What is left out of this list?  Or what would you change?

Meta Networks and Global Transformation – Basic Case

Meta Networks are:

  • Decentralized networks of people, organizations and networks,
  • Bound together by shared goals, values, and experiences.

Mega organizations (like governments and corporations) are still important.

But the global problems we now face are too great to be solved mainly by hierarchically controlled mega-organizations.

Compared to mega organizations, meta networks are potentially:

  • More intelligent and adaptive.
  • More accountable,
  • Better able to bring about needed shifts in global awareness and behavior.
  • Better at distributing ideas, resources and talent to where they are most needed

Global-scale meta networks exist and are enabling great things.

But great as their achievements are, their potential is much greater.

That is, existing meta networks aren’t yet smart and coherent enough to accelerate positive global changes to needed tipping points.   Meta networks are fragmented; and most of the people and organizations in them remain hidden and inaccessible to any given person or organization with a need for more effective connections.

We need to do whatever we can to help meta networks realize their potential.

Next:  What do meta networks need?

See also:  Meta Networks and Global Transformation (March 2009)

How LinkedIn Scaled

On Friday I’ll be attending an all-day workshop on “How Ideas Scale” hosted by Plexus Institute.   In thinking about that, I also began thinking about how LinkedIn scaled.  (I worked at LinkedIn in its first few years.)

LinkedIn now has 35,000,000+ registered users and continues to grow rapidly.   This is a big number, but not as big as Facebook or MySpace.   And yet because LinkedIn has focused from the beginning on providing value to professionals, the comparison with more social sites like Facebook isn’t so valid.  Getting 35 million busy professionals to participate is a big achievement.

LinkedIn began in early May of 2003.    At that time there were other professionally-focused social network sites that had a head start and were much better funded.  None of those companies are now anywhere near as successful as LinkedIn.

Here’s my take on how LinkedIn scaled:

  • Brought together a team of executives who had all worked with the principal founder, (and largely with each other) in previous Internet startups.
  • Kept the site simple and focused; didn’t overbuild, stuck to the knitting.
  • Gained its initial 5000 members almost immediately from the personal connections of the founders’ own personal connections.
  • A huge percentage of the first year’s members were influential social network early adopters who were primed to use the site for professional purposes.
  • From the first day there was an in-place data analytics strategy that enabled the company to measure effects and fine-tune the site design.
  • Stayed focused on its goals of growth, revenue, and usage as measures of value to users, as well as to shareholders.

Meta Networks and Global Transformation

In  a great piece written in mid 2007, Paul Hawken reminded us that there is a global meta network (he didn’t use that term) of people and organizations who care deeply about the planet and are working to save it.

He called it the planet’s immune system, now emerging to help us fend off multiple pathologies and terrible threats.

He also said:

  • It’s a decentralized network, not an organization.
  • There is no single hub. (That is, it’s a multi-centered network.)

  • It is not a conventional “movement” where everyone recognizes the same leaders and identical ideologies.

  • “People inside the movement can also underestimate it, basing their judgment on only the organizations they are linked to, even though their networks can only encompass a fraction of the whole. “

This last point is important.  It means that the network already exists, but it’s not yet fully accessible and usable.   Making the network more self-aware and usable is now what is needed, as described more below.

Immune systems are adaptive networks.

Brains are also adaptive networks, which is why many others have also called our interconnected global networks a “global brain.”   Hawken was especially pointing to the part of the global brain that reacts to rigidity, fragmentation, and decay – including abuses of power and environmental threats.

But this same network — people who care about the vitality and prosperity of the whole Earth — is more than just an immune system.  It doesn’t just fight things (disease and injustice, etc.).  It also creates knowledge, tools, and opportunities for growth and fulfillment of individuals, organizations, societies, and (yes) life on earth.

It is really a global network of transformation.

Except, it is not quite all wired up yet.

So, what does a globally intelligent Meta Network need to more fully wake up?

It needs at least these things, which are already available in some form or another, yet still developing:

1. Methods and tools for getting knowledge, talent, and capital to the right people and organizations at the right time.

This includes:

a. Communication tools and social media

We are now swimming in these, and constantly inventing more.

b. Tools for intelligently filtering messages and requests.

This includes tools for reputation, due-diligence, and brokering trust.  Baby tools for these functions now exist.  They need to be much more intelligent and pervasive.

c. Social networking platforms for sharing social capital and trusted referrals

The right tool will need to both enable continuously updated, searchable user profiles and searching the “social graph” for trusted referrals.

d. Network Weaving

Network weaving, and training for network weavers, can help make networks ‘smarter.’ Smart networks have shorter and stronger connection paths that are most useful to network members.   This means that searches will result in more relevant results, and it will be easier to find trusted and influential introductions.  In a smarter network the overall trust will also be higher and knowledge and ideas will flow more quickly to those who need them.

2. Collaboration methods, and the training & experience needed to use them.

E.g., methods such as Dialogue, Appreciative Inquiry, TRIZ, ToP (technologies of participation) and forty or so other especially useful ones.   This is crucial because echo chambers (talking to ourselves) and the inability to communicate effectively (creatively rather than destructively) are killing us.

But this is also especially challenging.  How do we get this, the ability to think productively together, to scale, to become truly pervasive?

To get people to think more constructively together requires not only good methods and training, but also a shift in the consciousness of individuals, for example, developing a level of consciousness that is bigger than their own egos.   To be sure, there are techniques and training for that as well.   Above all, we will need ideology-free techniques as well as traditional techniques preferred by different groups.   However, techniques that help people think together with others who have different backgrounds and opinions can also help bring about a shift in consciousness towards greater openness.  Openness is a great antidote to the bad effects of small egos focused on oneself or a single group.  For more on the connection between collaboration and consciousness see David Bohm’s On Dialogue.  His work is brilliant and his methods are solid; but unfortunately he doesn’t tell us how to make the methods scale.

How do we bring this about? Continue reading ‘Meta Networks and Global Transformation’


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