Archive for the 'Social Media' Category

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.

Advertisements

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.

Expansion of choices reduces diversity???

I just read an article from The Nation, by Colin Robinson (via Alternet.com):

How Amazon Kills Books and Makes Us Stupid

In summary, Amazon’s dominance of the book market and their intense drive to reduce the costs of books are having these effects:

  • Drastically reducing the number of independent book sellers.
  • Reducing the income of publishers, and especially authors.
  • Making it more and more difficult for authors to produce well-crafted and thoroughly researched books.
  • And reducing cultural diversity by overwhelming customers with choices.

This last point is the most surprising – and sounds the most paradoxical.  How could more diversity of choice reduce cultural diversity?

Embedded in the middle of the article is this explanation:

According to industry statisticians Bowker, just over 172,000 titles were released in 2005. Last year “traditional” output had risen to 288,000 titles, a significant enough increase by itself. But adding what Bowker describes as “self-published” and “micro-niche” books, the total inflates to a staggering 1 million new titles in just twelve months.

“Many would argue that the efflorescence of new publishing that Amazon has encouraged can only be a good thing, that it enriches cultural diversity and expands choice.

“But that picture is not so clear: a number of studies have shown that when people are offered a narrower range of options, their selections are likely to be more diverse than if they are presented with a number of choices so vast as to be overwhelming. In this situation people often respond by retreating into the security of what they already know.

“As Barry Schwartz, author of The Paradox of Choice, explains, ‘When the choice set is larger, people tend to make worse choices. They choose on the basis of what’s easiest to evaluate, rather than what’s important to evaluatethe safe, highly marketed option usually comes out on top.’

Actually, this phenomenon isn’t really the fault of Amazon, but is rather part of the effect of making it easier and cheaper for individuals to create their own content, i.e., to self-publish.   It’s of course not just happening in the world of books, but in all manner of media and content, including newspapers, reporting, editorials, and reviews, film, video, and photography, music, etc..

This is an incredible expansion in creativity and expression; and at the same time, this expansion has clear effects of creating echo-chambers where we, “the masses” who are now “personalized” are clumping together like never before and having less and less thoughtful exposure to ideas beyond those that we ‘naturally’ prefer and seek out.

So these are not new reflections.

But still, what are the answers?   How can we break through this paradox of explosions of expressions and choices that somehow create an implosion of diversity and dialogue?  (Actually, it’s not an implosion of diversity, as much as an explosion into huge and small fragments that appear to have not much to do with each other.)

Somehow the “answers” will have to be the creation of common experiences that invite curiosity, openness, and simple kindness.   Curiosity mixed with kindness can bridge differences, without eliminating differences.

What kind of experiences would these be?

As a designer of social technology, I can only think that, among other things, these experiences have to include radically new ways  a) to manage attention overload without killing serendipity, and b) to discover “content” that is rewarding – even deeply fulfilling – without relying on naturally clumping algorithms like “Show me more like this one” — or “Show me – books, movies, ideas, etc – that other people like who like the same kinds of stuff I like.

Honestly, with algorithms like that, what can you expect other than bigger and bigger clumps?

Facebook in the toaster?

I enjoyed Valdis’ latest post about Facebook:

Facebook is Toast

But I also disagree that Facebook is toast for the reasons that Valdis gives:

Facebook, and all other online social networking sites are structured wrong. They are places where we have to go to connect and communicate. That is not how we naturally connect and interact as humans!”

I do agree with his point that:

“…we decide on the fly, who to talk to, in what voice, and how much to share. I may deal you differently tomorrow than today depending upon the current context. “

And I agree that:

“In a truly networked world we do not have to go anywhere to connect to others — we just ping from where we are at and wait for the response from where they are at.”

And I also agree that there is still something that feels artificial and a little frantic about many elements of social media.

But I don’t think that makes Facebook toast.

For one thing, Facebook has been very busy in these last two years making Facebook more ubiquitous, so that micro updates and other content posted on Facebook can appear elsewhere, and vice versa.

In addition, the millions who use Facebook frequently — and similar social media — are actually adapting their behavior  and cognitive processes  to the new media.   So it’s a bit anachronistic to say “That is not how we connect and interact as humans!”   The ways we connect change as technology and culture change.   (Though if  we change ourselves too much, symptoms of fatigue such as lack of focus accumulate.)

I personally don’t use Facebook very frequently, and I find it way too cluttered, and too full of micro updates and chaff.   And I don’t like its privacy boorishness. And yet, I still think Facebook has good uses and I like having it around.   E.g., my son and several of my friends and other family use it a lot and it is a good additional way to stay in touch.

But there are millions of people using Facebook who aren’t like me and who use the site a lot more than I do.   If Facebook starts sleeping on the job, or makes a series of garish mistakes, that could cause it to quickly fade.  But otherwise, I see Facebook staying on the scene for quite a while.

And yet, in agreement with Valdis’ points, I’m definitely looking forward to new social media apps that feel more real, and that more intelligently adapt to us as thinking, feeling, and reflecting humans, rather than making us adapt to them.

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?

How to Use Social Search to Find an Angel

Here is a meaning for “Social Search” that is a bit different from the applications that Google, Bing, Facebook and others are racing to perfect.  This one is already available and can be really valuable to entrepreneurs and other professionals.

I have a new friend (who found me on LinkedIn) who is self-funding development of a very interesting new product and Web service.  (A prototype of the product is cellalert.org – but an advanced version is now in development.)  The existing product has received finalist recognition in netsquared and other mobile challenges.  He and his partner (in different cities) are both working full-time in senior level high-tech jobs.   He has received some small funding amounts but will need more in a few months to keep going.   He needs an angel, but not sure how to find one.

My suggestion is to use LinkedIn; and I’ll give some examples below that can help him and maybe others.

From my own experience with social networking platforms, LinkedIn is way better than any other platform for this kind of thing, where a trusted introduction really helps, e.g., for finding partners, investors, donors, advisers, employees, friendly press contacts, etc.   But I would love to hear if others have had good results with other platforms.

OK, how to find an angel: Continue reading ‘How to Use Social Search to Find an Angel’

Social Search – What will float to the top?

Social search is on big companies’ minds:
Google’s New Social Search Is A Big Chess Move Against Facebook (ReadWriteWeb, 10/21)

So, Bing has Facebook and Twitter, and Google only has Twitter.

Where is LinkedIn in this conversation?  LinkedIn’s news sharing is worth looking at.  With a few changes it’s potential would be actually greater than either Twitter or Facebook updates.

Why is Twitter so useful?   Because I can choose whom to follow, and others can choose whether to follow me.  But Twitter has big limitations.   Even by creating a selected group of the people I’m following I still have to wade through a lot of non-relevant stuff, and I *mostly* miss a lot of stuff that disappears below the horizon surprisingly quickly – because I look at Twitter at most 2 or 3 times a day, and often go days without looking.   Also, 140 characters is very neat.   But not always appropriate.  It doesn’t really tell me enough in order to decide accurately whether to click through on the links.   And they don’t contain enough info to store and search.

I like LinkedIn News because I can quickly grab content from the Web and share it.  If I want to share it with a particular group or group of connections, this is great.  But something really crucial is missing.

I don’t always want to *push* news and ideas I find interesting to a particular group or set of connections.  And I definitely don’t want to spam all my connections.   I *do* want to be able to collect news and ideas and keep the items in a single place.  And I *do* want to be able to follow/subscribe to collected news and ideas from a selected group of connections and non-connnections.  And I want to also be able to go to a single person’s profile and see what news and ideas that person has collected, or to search my connections for news and ideas that match specific tags.

Those changes would make LinkedIn News much more powerful than either Facebook or Twitter updates – precisely because LinkedIn is much more focused on professional value rather than also flooded with personal messages, photos, etc.  Plus, LinkedIn profiles tell me much more than Twitter bios, and after all, I already have a lot of important connections on LinkedIn.  So LinkedIn’s search capabilities could allow me to find people who share my interests *and* who have impressive profiles and recommendations *and* who are sharing news and ideas from the Web.  This would be doing what LinkedIn does best.


Archives

Share this blog

Bookmark and Share

Categories

twitter.com/duncanwork :

Error: Twitter did not respond. Please wait a few minutes and refresh this page.

Advertisements

%d bloggers like this: