The real life social network – questions about boundaries

There is no such thing as “friends”. That’s the most powerful conclusion in an excellent presentation about in-depth research by Paul Adams, UX researcher at Google. Most people tend to have 4-6 groups of friends, each of which has 2-10 people, and there is typically very little overlap between them. These friends represent different life stages and interests. A person’s large “friend list” on a service such as Facebook or Twitter actually consists of a handful of close friends and family members, in different groupings, plus a much larger number of casual friends and acquaintances.
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As Mary Walker observed on Twitter, “Each person=many roles (family friends career hobbies) but social networks suck @ helping ppl manage this.” Mary was summarizing this post by Deanne Leblanc. The mismatch between the affordances of social tools and the shape of our social lives has been observed by many – and Adams’ research quantifies that mismatch.

In software design, the common usage patterns need to be very strongly supported – and in Facebook it’s definitely not. Paul Adams reaches powerful conclusions that would result in social software designs very different from Facebook, which has very poor control over what to share with whom, and poor control over how to present oneself within different social contexts.

Follow up questions: social boundaries

The presentation is excellent, and the research looks well-done – and I also have some follow-up questions about the results. The presentation concludes that there is very little overlap between groups of friends. But, I wonder about that overlap. What is the role of the people who span groups, co-workers who share an interest in a sport, fellow parents who are involved in local politics? From the perspective of the spread of information, culture, action, do boundary-spanners have extra influence?

Also, the presentation observes that people’s friends change as their lifestage and interests change – but the presentation focuses on the static picture at any point, rather than the changes. How do these changes happen? How often do social connections play a role in the changes? Focusing on the changes and transitions, rather than on the patterns of stasis, might yield interesting insights on secondary patterns to support.

The example in presentation, about sharing that unintentionally crosses boundaries, is about a young woman who comments on photos of her friends in a gay bar; these risque photos are exposed to 10-year-old kids she teaches. In Twitter, Paul acknowledges that the friends being gay isn’t the problem, sharing pictures of adult sexuality with kids is the problem – and editing the presentation to make that distinction clear would be good to do.

In that case, partitioning is the right thing to do. But there are many other examples of sharing where the problem isn’t sharing stuff that is inappropriate for a social context, but where it’s uninteresting to some . Is it possible to design a system that makes it easier to improve the signal to noise ratio without hiding information that doesn’t need to be hidden.

The presentation talks about the new social web architectural pattern where one takes ones friends with them across the web – for example, on, you see the stories your friends liked and commented on if you are logged into Facebook. But how should this pattern work, given that “friends” are not a single group. For a person long past highschool, is seeing the opinions about a high school acquaintance on a news story a benefit or a drawback? (This example is theoretical, apologies to any HS friends who may be reading this!)

One common theme among this set of questions is about the boundaries between strong and weak ties – how can software do a better job of supporting strong ties, while enabling a semi-permeable membrane for people to people and communication to cross those boundaries. Of course (and the presentation does a good job of reminding) is that the relationships are amongst people, not tools. Boundaries are shaped and reshaped by people in our interactions; tools can help or hinder but they don’t create or destroy.

A different social network

Recently there’s have been rumors that Google is going to come up with a new social network that is a Facebook clone. I really hope that Google doesn’t simply clone Facebook, and instead that they use the insights in Paul Adams’ research to make social network tools that are different from Facebook, and better suited to how people’s social networks function.

Information vs. conversation?

This Edge blog post suggests that Facebook’s problem isn’t that it violated people’s expectation about privacy, but that it’s trying to change the social dynamic on the site from conversation between friends and family to sharing information. I think this distinction is misleading regarding people’s communication, Facebook’s strategy, and Twitter’s strategy too.

The article argues that Facebook was initially set up as a way to talk with friends and family. But the new default-public settings make it more of a tool for sharing information. A lot of what people do on Facebook is to share stuff – photos, links, videos, etc. Thing is, that sharing is social activity – people sharing stuff with family and friends. This sharing on Facebook is increasing rapidly – the stats in the Inside Facebook article don’t say why, but I very strongly suspect it’s because Facebook has made sharing very easy, not because people are suddenly thinking themselves as publishers.

By contrast, Twitter’s leadership has seen Twitter as more of a broadcast platform. Features like follower counts and the retweet feature supported that strategy, and did less to support conversational use. (The retweet feature removed the ability to add a comment, and emphasized the number of times the tweet had been shared). But recent speculation is that they might come out with conversation threading, which would make conversation easier.

I think that the perceived polarity between “sharing information” and “conversation” does everyone making and using social tools a disservice. When there’s two-way communication, people share information and talk to each other. That was the initial insight about social objects from Jyri Engestrom. One of the cultural fundamentals in the modern world is that people socialize around common interests, symbolized by things we share with each other. Sharing bits of content doesn’t mean we’re being less social, it means we can share a clip when we talk about a sports game or a link when we talk about a news story – familiar types of social conversation.

The experience around social objects has several elements – who you think you’re talking to (as danah boyd and Kevin Marks described), the affordances for sharing the object (where Engestrom focused), and the ways the dynamics of listening and interchange work and are visible to participants. (where Adrian Chan focused).

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The problem with Facebook’s changes and clumsy user experience to set levels of sharing are about Facebook trying to influence people’s decisions who they share with, and proliferating confusion about who people share with. They messed up the “who I’m talking with” attribute. Twitter’s focus on the competitive aspects of talk hampers the social dynamic of sharing. Information and conversation go together. There are design and business opportunities in getting the blending right.

Realizing Robert Scoble’s vision of the end of social information silos

Last week, Robert Scoble wrote Location 2012, an excellent blog post where he illustrated a vision of a world where location-based services could work together instead of being information silos.

Services including FourSquare, PlanCast, Tungle, Glympse, and Siri work together to notify Scoble’s friends where he is and where he is going, so they can meet each other instead of missing each other. Services such as Blippy and Expensify share Scoble’s financial data on his behalf.

To make this happen, you need to be able to follow the same person’s activities across a variety of different services. You may want to be able to share updates with sets of friends with common interests across platforms. Updates need to encode location, so the application can present what’s geographically relevant. Apps need to share data, without a user’s needing to keep and enter many different passwords.

The cool thing is, the technical standards and protocols to make this vision a reality are starting to fall into place. ActivityStreams are an important part of the mix. ActivityStreams are a standard way of representing common social actions, like posts, follows, likes, and checkins. PubSubHubBub/Webhooks allow applications to subscribe to updates from other applications in realtime. WebFingeris intended to let you find the same person across social sites. Portable Contacts is intended to represent a set of people – a contact list or subset of contacts. Oauth is used so that applications can gain authenticated access to other applications on the user’s behalf.

I’ve illustrated Scoble’s scenario below – the amazing thing is that it could all be real today! The only piece that hasn’t been worked out in the standards stack is the ability to create that upcoming Facebook event. Everything else could be implemented now.

The central concept in making this vision is real that “social” is not a set of silo’d services with social features – it’s a layer that crosses multiple services. The best way to bring this world about isn’t to wait for Facebook to implement every possible social feature, but to build in the standards support and interoperability to make many services more useful for all.


This Prezi by Kevin Marks has more on the emerging standards stack – thanks to Kevin for review.

Conversation curation

In a couple of good posts, JP Rangaswami reflects on the need and opportunity for democratized curation. He cites Google CEO Eric Schmidt quantifying the incredible amount of information being generated on the internet – these days, 5 exabytes of information is created every two days, as much as all the information created between the dawn of civilisation and 2003. JP writes about the need for curation of text, music, image, and video. I’d like to focus on a new opportunity – curating conversation.

The last few years has seen the rise of the realtime web, so-called status updates in Facebook, Twitter and other services, much of which is really conversation. The stream flies by quickly. If you missed it, it’s gone. Search of stream content is getting better, but even so, if you find a single message, you don’t really get the gist of a conversation. This is where curation comes in. This is different but closely related to “tummeling”, which is the art of facilitating a live conversation in process. Conversation curation is the art of representing and summarizing a conversation, so others can see it later, and the conversation can pick up again from a new starting point.

Conversational curation isn’t needed or wanted for many conversations – sometimes the conversation is truly transient – for example, nobody needs an edited record of people cheering their team through a hockey championship. But sometimes conversation does have longer-lasting value. For example, there was a fascinating Twitter conversation between Howard Rheingold and his Twitter followers about attention and distraction. This discussion contained information and arguments that seemed worth preserving, so I wrote it up as a post, which has continued to get references well after the original discussion. People have been using the practice of summarizing conversations in mailing lists and forums for years. The realtime web makes this practice more important because conversations can be even more transient and hard to piece together without a curated record.

There are some very old, pre-modern examples of the form of curated conversation – found in the Talmud and, I’m told, ancient Chinese traditions also. In the Jewish tradition, the form of curated conversation comes from attempting to preserve some of the texture of an oral tradition of dialog and debate, as that tradition was being represented in written form.

This is one of the reasons why I’ve been interested recently in modern takes on the representation of multi-voiced discourse in ancient works – because I think that this old form has lessons for a new need in quite a different cultural context. An edited conversation, with multiple voices assembled by an editor, is not identical as a live conversation in which participants speak for themselves. Scholars looking at the old forms debate how much the edited conversation is actually conversational. Daniel Boyarin argues, building on Bakhtin, that the editor’s hand smooths out differences in the represented voices and turns the dialog into a monolog. But David Frank contrasts the dialog in Plato, where the conversational partner is represented merely as a foil to reach a foregone conclusion, with dialog in the Talmud, where the different voices carry different ideas, and the whole picture includes multiple voices.

Another distinction – and something that may be important for the future genre – is how readers are brought into the picture. With the Talmud, says Marc-Alain Ouaknin, the dialog is represented – and culturally presented – in a way such that readers are drawn in to converse together in realtime to carry on the conversation, in debate with each other, adding their own contributions. By contrast, in Socratic dialog, the reader is expected to understand, assimilate, and agree with the presented conclusions.

In a new book that looks at these ancient forms of represented dialog (that comes to different conclusions than David Frank, and than I do agreeing with Frank), Daniel Boyarin makes an important point. Representing a conversation doesn’t freeze it, it just pauses it. The transition between speech and writing is a repeated cycle – “written culture becomes transmuted into oral culture and then back… over and over and over again.” Part of the form of curating conversation will be representing it in a way that people will find it welcoming and interesting to continue the conversation in realtime, and continue the cycle again.

Another important difference from the pre-modern forms is the boundary of the conversation. Daniel Boyarin notes astutely that the conversation represented in the Talmud is open with respect to ideas seen as within the community of the Talmud’s rabbis, but closed with respect to ideas seen as outside that framework. In modern settings, people create boundaries for conversations in very different ways – but those boundaries still exist, often as informal social norms. In communities of fan fiction, participants decide what works fit into the canon they will remix. In political communities, participants decide which opinions are legitimate for debate in a given community, and which positions are out of bounds. The editors / curators will play key and controversial roles in maintaining these norms.

There are some emerging technical components that will make the practice of curating conversation easier – to conduct conversation across services, and Salmon to pull together the comments. Plus, perhaps, there is a need for visual editing tools to pull the pieces of a conversation together.

In the world JP Rangaswami envisions, where curation is an important part of improving the ratio of signal to noise, conversational curation will be an important art, and the cycle between live conversation and the edited representation of dialog will become important once again.

The game is the frame: what realworld software can learn from games

Sebastian Deterding has put together an attractive and substantive presentation for UXCamp Europe, exploring the principles of game design and how these principles may or may not be applicable to software design. Historically, user experience has focused on tasks and efficiency, not fun.

To cut to the chase, Deterding concludes that software user experience is fundamentally different from games, for two reasons. Most importantly, what makes games fun is that they are voluntary and have no real-world consequences. If there is obligation or consequences, then the fun goes away. Secondly, in a game, the designer controls the tools and the goals, but in realworld activities, the designer is traditionally very remote from the actual goals. At work, the goals are set by managers, by the needs of the company for things like sales and solving customer problems – not by the software designer.

To first order, Deterding is right, and this explains why the application of game design principles to realworld activities often falls short. Social software “game-design” systems that reward users for actions like making blog comments – actions that are meaningless by themselves, and become drudgery in a realworld context.

But I don’t think game principles apply only when there are no realworld consequences or obligations. For example, fundraising campaigns have long used public thermometers and social competition, for the realworld goal of supporting nonprofit causes. People participate in these programs as volunteers – it’s not the same kind of obligation as a job you’ll be fired from if you neglect. But people participate with a sense of community obligation, and the campaigns build on people’s sense of social obligation to each other. In a particular community, someone can choose not to participate, at some real cost to community standing.

To give another example, Chris Messina gave a recent talk, where he explains how he used game design practices from Flickr in helping to design and promote a campaign to spread Firefox, when the open source browser was a scrappy newcomer gaining recruits against incumbent Ineternet Explorer. The campaign had explicit tools that helped participants climb a ladder of activity, and meet their personal goals by meeting the goals of the Firefox project.

Ladder of participation, SpreadFirefox campaign

So I don’t think that a game needs to be free of realworld consequences or obligations. But the game needs to be aligned with those consequences and social dynamics.

The other issue that Deterding raises is that software designers are traditionally far removed from realworld goals. This is true – and this is something that needs to be fixed for game mechanics in realworld games to be anything more than window dressing. This means that tools need to be configurable to provide much more control to the people with real world goals, to integrate them into the experience.

Deterding reaches a similar conclusion to John Hagel, John Seely Brown, and their team at Deloitte, from a different direction. They argue that social software in the enterprise is bound to fail, unless and until it is connected to the realworld business goals and metrics. And this is going to be a key focus of the next generations of business social software.

Unlike Deterding, I don’t think that fun is orthogonal to realworld impact. But fun in a real world context is enabled (or, more often than not, removed) by social dynamics – by leadership and culture. And by the degree to which the goals of an organization align or thwart the goals of participants. Tools can’t do these things, can’t fix them if they’re broken, can’t add them if they’re missing.

So, I agree with Deterding that the shallow use of game dynamics doesn’t do much good for software for activities with realworld consequences. I am more optimistic than Detarding about the potential, but only when the goals and social dynamics, leadership and culture are aligned.

I strongly recommend the presentation if you are thinking about this topic – the presentation walks through elements such as clear goals, bite-sized actions, scaffolded challenges, and social comparison that make up a game, has good comparisons and contrasts with software design, and has good resources for further learning:

The strong and weak case for social objects

Adrian Chan wrote an interesting blog post last week arguing against the common notion of the social object. I think Adrian’s mostly right. Social objects are useful, but the arguments in favor of social objects are made way too strongly, blinding designers to a wealth of opportunities that support the interactions surrounding objects, and not just the objects themselves.

The idea of social objects was crystallized in 2005 by Jyri Engestrom, building on a 1997 academic paper by Karin Knorr-Cetina. Later on Rashmi Sinha created an excellent presentation elaborating on many aspects of the overall social object design pattern.

In comments, Jyri makes a categorical case that “the object gives us a reason to talk to each other.” This strong version of the argument fails. Jyri brings the example of Linked In, a social network where people don’t simply connect to connect, they connect because of a social object, a job that binds them. But even this seemingly clear and sensible argument about LinkedIn doesn’t work very well. Even in Linked In, the interactions aren’t mediated by “a job”, but an industry or field, and topics and informally defined communities within that.

The weaker form of the case for social objects is valid – if you are a LinkedIn designer you definitely want to enable people to represent their jobs and find others who are co-workers or alumni. But the strong case fails. In fact, using the design pattern in Linked In overly strongly causes a design failure, and is the reason that I often use Facebook or Twitter instead of LInked in to represent a professional connection! Linked in requires you to say how you know someone within an explicit taxonomy – a job or institution. But if I know someone within an informally constituted social design community, say met at a meetup, I need to know their email to join on Linked in. And I don’t bother, I use Twitter or Facebook instead.

Even in Slideshare, which Rashmi Sinha designed around the idea of social objects, people are sharing objects – slides – within a variety of social contexts including conferences, marketing lead generation, technical standards development, humor, church sermons, that involve many sorts of social relations & interactions. If you are designing SlideShare, you want to look closely at the object to figure out common things that people want to do with slides presentations, such as rate and comment. And then you might want to look at the broader set of interactions for other ways of providing value to people – such marketing lead gen tools, or conference-related services.

As Adrian Chan observes, what’s meaningful isn’t just the object, but a set of social interactions and practices that surround the object. An excellent example of objects that subordinate to social dynamics is the story of Farmville. What’s compelling about the design of Farmville – what makes people obsessed with playing it – isn’t the game tokens, but the set of social obligations around the exchange of these tokens. Another example is the use of Formspring by teenagers to harass and bully each other, see this post by danah boyd.

Out of curiousity, I went back and read the original Knorr-Cetina article, and was not persuaded by her theoretical case that objects are in fact the center of sociality. The article used broad sociological generalities – people are alienated individuals in a knowledge economy – to make the case that objects have now become the elements that draw people together in the absence of other social ties.

In her focus on objects, Knorr-Cetina appears to ignores large swaths of history, sociology/anthropology and social theory about the social practices that bring people together. She writes “in a knowledge society, object relations substitute for and become constitutive of social relations… for example, objects serve as centering and integrating devices for regimes of expertise that transcend an expert’s lifetime and create the collective conventions and moral order communitarians are concerned about.”

But there have long have been social conventions and processes and bodies of knowledge in various fields. The transition to modernity extracted knowledge from heritable social structures into subcultures that are communicated through networks and institutions with greater social mobility. Just to pick one quick example, Elizabeth Eistenstein did a good job of writing about this transition in the context of the spread of printing. But Eisenstein wrote that printing and books facilitated these changes and practices, not that books *were* the changes and practices. Why use specific objects as synechdoche for the swath of the practices, networks and institutions that enable knowledge discourse?

Perhaps there is some academic or theoretical context that I am missing, which makes the article more meaningful than it appears. In any rate, going back to the source does not seem to provide justification for the “strong case” for social objects, which is that they are *the primary cause* for people to communicate, rather than being part of a matrix of practices, relationships, and things. The now-familiar social object design pattern is good and useful – it doesn’t need to be done away with, but it is limited, and there are more aspects of social design that become visible when one considers the interactions around the objects.

The problem with Facebook Like

The problem with Facebook Like is that it breaks Activity Streams and instead tries be the sole provider of social context.

Currently, activity updates are tightly bound to the service in which they were created. In order to share with others, the choices are blunt – annoy all your Facebook friends with game updates, annoy all your twitter followers with 4square checkins. By giving activity streams a standard vocabulary and metadata, applications will gain the capability to create more refined – and contexually relevant – posting choices and reading filters.

But that’s what Facebook’s “Like” gets rid of. See, there’s an alternative vision about social context. And that is that Facebook is your one and only source of context. Thomas Vanderwal suggests, in the discussion of Facebook’s recent announcement, that Facebook is not doing such a great job of this today: “The social graph is dangerous without context and much more dangerous w/ partial context.” ActivityStreams fosters competition among services that want to provide social context of various sorts, and Like forecloses that competition.

Elias Bizannes does the technical analysis to support this conclusion in an excellent post on the Data Portability project blog which analyzes the open-ness of Facebook’s Open Graph Protocol. Bizannes writes that:

the proposed page header metadata “a play to increase the quantity of semantic data on the web and then capture social gestures (aka “Likes”) made against those concrete semantic objects – think a web-wide recommendation engine. This is a big step forward for Tim Berners-Lee’s vision of the semantic web.

Currently, however, these gestures are submitted to FB’s proprietary database using proprietary API calls. This was not the most open way to execute on this functionality. Instead, these gestures could be written out to a site-specific Activity Stream that can then be indexed by any web-crawler.

There is a simple way for Facebook to remedy this situation, which is to support the Activity Streams standard for like updates. In this way, Facebook could compete to actually be the superior provider of social context – it has a major opportunity here – without closing off competition to other sites, tools and services.

If Facebook doesn’t do this, the challenge for those who’ll benefit from competition is to make it very easy to support standard activity streams – and then use that data to actually do a better job than Facebook at supporting the social desires of users

Social recommendations and the Eliza Effect

In a post on on Algorithmic Authority one of Adrian Chan’s key points is to displace the critique of the authority claim from the recommendation itself to the users’ acceptance or rejection of the recommendation. “Authority, in short, depends perhaps on the user, not on the algorithm, for it is only on the basis of the user’s acceptance that authority is realized. It is subjectively interpreted, not objectively held.” However, there are a number of problems in severing the communication from its reception.

The example at hand came from Facebook’s flawed friend recommendations. These suggest that you friend or re-contact people, apparently based on an analysis of your social network and communication patterns. These recommendations are particularly annoying because of visual design, and even more so because of social design. The recommendations are featured prominently in the interface, and impossible to suppress without effortful, power-user techniques like Greasemonkey scripts. The big problem is social design. Dennis Crowley, co-founder of Dodgeball and later Foursquare, described the classic flaw with social network based recommendation as the “ex-girlfriend” problem – when an algorithm detects a person that you haven’t communicated with in a while, there is often some very good reason for the change in communication pattern.

The flaw in social network based friend recommendations is related to Adrian’s recent critique of social network analysis. The social network map is not the territory – the visualization of lines of connection based on explicit communications leaves out critical information about the directionality and the content of the communication. A gap in communication may be an unintentional lapse in attention or a rupture; frequent communication may be a sign of closeness or flamewar.

One problem with this misreading of social network analysis results is that the more personalized and personal recommendations, the more likely they are to trigger the Eliza effect, which is “the tendency to unconsciously assume computer behaviors are analogous to human behaviors.” The more a computer impersonates human, the more people will tend to anthropomorphize the computer, and have a strong emotional response to that computer which acts as a human. The converse reason for a strong emotional response to a poorly personalized recommendation can also come into play. The “Uncanny valley” is the name of the disconcerting effect when computer simulations that are nearly but not quite human. People find simulations that are close to human much more annoying than simulations that are more cartoonlike.

It is risky to simply dismiss the effect of pervasive messages, even messages that are not acted upon. Marketers have long considered the psychological effects of communication; marketing messages and frames affect consciouslness even if the listener does not take immediate action, even if the listener superficially ignores the message, even if if the listener superficially disagrees.

You can’t unsee and you can’t unhear. This effect is most visible at the extremes; thus the disturbing effect of chatroulette, the random-navigation chat program that has attracted people in search of random conversation and entertainment, and plenty of flashers. If someoene doesn’t want to see the private parts of random people they should stay off chatroullette; clicking past the flasher doesn’t solve the problem, because you can’t unsee.

Sure, bad social system recommendations are merely annoying; they don’t make us take any action we don’t want to do; but just because we haven’t taken action doesn’t mean the recommendations have had no effect.

The holy grail of internet marketing has been to make recommendations that are powerful and compelling because they are personal, based on a wealth of information based on the user’s personal behavior and actual social network. The lesson for social designers is that it is possible to make recommendations that are not-quite-right, that are more annoying to users because they are more personal. Being personal can be touchy; requiring care and caution, and avoiding overconfidence.

Adrian’s post on Algorithmic Authority has a broader scope, dealing with the larger sociological implications of the idea of algorithmic authority proposed by Clay Shirky, and refining some distinctions on the topic I proposed here. If you haven’t read it, it’s worth consideration.

Trust is contextual

As healthcare reform passes, I’m having a strong but respectful disagreement with a friend over twitter on the nature and impact of this change. I know him through professional circles and I’d recommend him for jobs; and I’d trust him to pick me up on the highway if I was stuck in his town. But I wouldn’t trust him for advice in political matters. There are friends whose political judgement I trust and seek out, but whom I wouldn’t trust to take me to a concert or a movie I’d like. There are people who’s advice I’d take personally but not economically, and vice versa. Trust is faceted. Trust is contextual.

Craig Newmark, who combats untrustworthy behavior every day on Craigs list, believes that distributed trust is the next big problem for the internet to solve. If Google, Facebook, and Amazon got together, they might be able to address this problem of untrustworthiness online. Jay Rosen, who I trust and think is wise about many issues, agrees a distributed trust network is needed.

I am a huge fan of distributed solutions to many problems, but not this one. Trust is contextual. Even trust within a specific online service can’t be generalized. The other week I was scouring the music recommendations of a prolific Amazon reviewer with deep musical taste in areas I like. That same reviewer’s opinions about religion and politics are 180 degrees away from mine. He could buy me a recording sight unseen and I’d probably love it, but I couldn’t read most of his book recommendations without throwing them.

Bruce McVarish believes that the trusted circle will start with people we trust in real life. But even in a close personal circle, trust is contextual. Even among my family and closest friends, there are different people I would trust for different things.

Trust can be extended along specific and faceted lines. In the important area of transactional trustworthiness, ebay-style ratings are critical. A distributed solution for transactional trustworthiness could be quite useful. It would be handy to have distributed trust metrics that could be extended across services in a given domain – I’d love to follow the Amazon music recommender across his various music services on and Spotify and so on. But trust in any one domain doesn’t extend to other domains. Someone might be a meticulously reliable seller of used books and electronics, but they might be a horrible filter for news, which is the area that Jay Rosen cares about; or they might be personally unkind, so wouldn’t make personal trust list.

There is no general distributed trust solution to be had. Trust is always contextual.


Update 1: a few more thoughts, in response to some questions on Twitter and in comments

Trust, here, is the inverse of reputation.

For the facets of trust where there might be some tractable technology help, the facets need to be addressed with different kinds of technology augmentation.

* In the area of transactional trust – do I trust you to deliver this used book on time in the condition you promised – trust may be represented as a number. If your trust score is 99/100 I’ll buy the book. If your trust score is 62/100 I won’t buy the book from you.
* But in the context of opinions and tastes – would I like your movie recommendations – the number is not so useful by itself, but only as an indicator about similarity of opinion. So, if an algorithm says that our tastes are 75% similar, then I may want to subscribe to your movie recommendations.

So, for transactional trust, a distributed trust solution might aggregate a reputation score. For opinion trust, a distributed trust solution might calculate a score based on actions in multiple services, but then aggregate the actions (like movie recommendations) across services.’s music similarity scale works along these lines already, based on aggregating listening information. Last allows users to scrobble their listening across services, shows how similar your taste is to others, and then allows you to explore the listening of these others.

Also, to anticipate another question, in social media, recommendations and other such trust-building actions are social gestures, not just quantitative ones. I recommend a movie to show off my own taste, to be generous to friends, to amuse, to give a gift, to express my similarity or difference with a public, and so on. And within this social dynamic, it would be helpful to be able to identify people who have enough similarity to want to share these gestures; to aggregate the identification across services, and to aggregate the recs across services.

Update 2 in response to comments from Thomas Vander Wal and Charles Green.

It’s important to consider that the set of circumstances where technology help with trust problems is really constrained. Both Vander Wal and Green spend much of their time helping with people to communicate better in groups – in these situations, the responses are largely about people, customs, culture, values, leadership, facilitation, tummeling. Tools are small part of the response, compared to the human aspects. Charles Green summarizes well: “The things that can be scaled up through numbers on the internet are important, but limited.”

From the perspective of technologists, numbers and tools are hammers, and social concerns may look like nails. Technologists tend to overestimate the set of problems that can be addressed by technology. Part of the job of those of us working in social software and social media is to be analytical enough, and humble enough, to identify the things that are tractable with metrics and tools, and those things that need to be handled by people regardless of tools.

Even the frame of “problems to solve” that technologists bring is part of the problem, sometimes. Even with good will, people are always different, with different perspectives and interests. Buber, Levinas (and other purveyors of wisdom) remind us that people being different is a fundamental condition of life and an opportunity, not a problem. Sometimes there is no “solution” because problem is often the wrong frame.

Diversity and social design

In a post last week, Adrian Chan called out claims that competitive motivations are predominant in human nature.

One such quote comes from Louis Gray, writing on the need for more meaningful metrics than followers. “Humans have this innate sense of need to be ahead of all others, to measure themselves, and deliver some level of self-assigned worth thanks to what are questionably valuable statistics.”

Adrian rightly observes that, “it’s not humans or human nature that are the cause of this. It’s systems and the design of social experiences and systems…. viewed empirically, societies around the world are organized in wonderfully different ways, manifest in a tremendous range of culturally diverse traditions and pastimes.”

People in different cultures have different preferences with about the expression of value and status. For example, the design pattern wiki for O’Reilly’s Designing Social Interfaces describes differing cultural preferences for ratings. “The very notion of a binary, black-or-white, love-it or hate-it ratings system may not be a natural fit for some cultures. Many locales have stated a preference for ‘shades of gray’ in a polarized scale. (Note this is subtly different than Star-ratings, which imply “I like it exactly this much.”)?

To remedy the situation, Adrian calls for a better understanding of social dynamics. The current understanding gap is exacerbated by a lack of diversity in social design; consciousness of diversity among the user community, and actual diversity among designers. The lack of diversity contributed notoriously to the Google Buzz privacy debacle – Google tested Buzz internally for six months, but Google’s employees – mostly young male engineers – were not concerned that the system exposed users’ list of email contacts. The social networks of Google employees were more homogenous and harmonious than the social networks of the gmail user base. As soon as the product was released, users with different experiences – people who were harrassed by stalkers – consultants who had confidential client lists – quickly objected to this disclosure.

Embedded in the practice of software design is the notion that “you are not your user”; designers need to consider the way that users preferences may be different from their own. Demographic diversity is the most visible sort of diversity – differences in gender, age, ethnicity, geography. Diversity isn’t just a matter of demographics; there are differences in personality and temperament that lead to different social interaction preferences. As social software and social media mature, designers and implementers will benefit from a greater understanding of differences in among users.

The need for diversity in social design is another reason to advance the development and adoption of standards. A monoculture of a few dominant vendors is less likely to generate a diversity of social software affordances that that will meet the variety of needs among social software participants. The spread of standards will make it more feasible to have a diversity of suppliers, creating a diversity of services meeting different needs and preferences.