Landing-like software from CUNY, based on Buddypress, intended to provide a learning commons with relatively little effort or configuration. It’s a nice bit of packaging, slick, with good collaboration tools and a simple, activity-stream-oriented social network. Commons in a Box is definitely worth looking at if you need a site to support a bottom-up social community or network, and you don’t have a wealth of resources to put into building your own. 

I came across this software because it is being used in the University of Brighton’s newly reborn community site at https://community.brighton.ac.uk which, until it was killed off last year, used to run on Elgg.  I remain a fan of Elgg for building such things, which has a lot more options than BuddyPress available by default, richer access control, and a much more elegant technological design that makes customization more robust and flexible, but this seems to be a great simple solution that just works without demanding much effort, and that, thanks to its WordPress foundations, could be customized to do pretty much anything you’d want a bit of social software to do. 

Address of the bookmark: http://commonsinabox.org/

A sad article, if ever there was one. This is about Google’s in-kind response to Facebook’s depressingly successful attempts to be a bigger and better AOL/Compuserve (amongst other things, through its ‘philanthropic’ internet.org arm, that people in developing countries afflicted with it sometimes think of as the Internet). The general idea is that Google will host content, rather than linking to it.

This is not the way the Internet should go, and this is not in line with Google’s avowed intent to not be evil. On the bright side, in real life, though poisonous and virulent, it is not the way the Internet really is going: the Internet is, ultimately, self healing, both in technical and in social terms. It might look like a fairly closed system to people that generally interact with it through Facebook or Google Search (or any of hundreds of thousands of other less successful attempts to lock people in) but it is heartening that WordPress dwarfs all of them put together in terms of sites and people that visit them (more than a quarter of all sites), and Worpress sites are, to a very large extent, controlled and owned by the people that run them. And that’s just the most popular content management system: the Web is many times bigger and more distributed than that, and the Internet is vastly bigger still. And, of course, Google is not the only search engine. You can find the rest of the Web in many other ways.

So, though the article claims doom and gloom all round, I remain optimistic that common sense and decency (or indecency if that happens to be your thing) will triumph in the end, and the game will never be over. A few successful parasitic corporations/applications – Facebook (including its subsidiaries like Instagram, Whatsapp, etc), Google, Apple, Amazon, Twitter, Snapchat, LinkedIn, Yahoo, Microsoft, Pinterest, etc – are doing their darnedest to wreck the open Internet, and are definitely shaping much of it, killing open standards, and sucking billions of people into their locked-in lairs, but those billions of people are just a click away (often, from within those systems themselves) to what the Internet is actually composed of, especially the Web side of it. Sure, these are parasites that suck the life out of openness and diversity but, like all parasites, they would be more than foolish to kill their host. And, hearteningly, the network effect (especially the rich get richer Matthew Effect) works just as effectively in reverse, as any former MySpace or Friendster afficionado will tell you. Or AOL, for that matter.

Address of the bookmark: http://www.salon.com/2016/05/01/googles_new_media_apocalypse_how_the_search_giant_wants_to_accelerate_the_end_of_the_age_of_websites/

I quite like the word ‘reactions’ that Facebook is using to describe their new options to express feelings about a post. I wish I’d thought of it. This is a matter of much more than passing interest to me as it relates closely to something that occupied a lot of my time over some years of my life. In my own CoFIND social bookmarking system (that first saw the light of day about 18 years ago and underpinned my PhD work) I used to refer to something quite similar as ‘qualities’ – metadata (tags) to show not just that something is good or interesting but how it is good or interesting, that could then be used to rate and thus help to filter and rank a feed of bookmarked resources. CoFIND is an acronym – Collaborative Filter in N Dimensions – that refers to this n-dimensionality of ratings. Facebook’s Reactions feature is a simplified version of this: it’s about categories more than tags, but the thinking behind it is broadly similar. The differences, though, are interesting.

Fuzzy ratings

One of the things that is most notable about Facebook Reactions is that ratings are, like its Likes before them, binary: a simple ‘yes’ or ‘not-rated’.  In most versions of CoFIND (it iterated a lot), users could choose to what extent something was good/loved/annoying/interesting/etc through a Likert scale. Giving the option to choose the strength of a feeling seems much more sensible when talking about fuzzy values like this. I want to be able to signify that I quite like something, or that is is mildly amusing, especially if my intent is to communicate my feelings to others. Facebook’s Reactions are a coarse as a means of expression: it is quite appropriate that its emoticons are literal caricatures.  In all the methods I tried – radio buttons, clickable links, etc – introducing scalar ratings turned out to be way too complex to be usable, but web interfaces were not as rich in those days: I think things like popup draggable sliders (not dissimilar to Facebook’s interface) might make it more feasible nowadays.

Evolving metadata

Facebook Reactions are not just binary but fixed. CoFIND – I think, still uniquely – allowed individuals to create new qualities (reactions), which could then be used by anyone else. It was an n-dimensional rating system where ‘n’ could be any number at all. Qualities quite literally evolved for each community, with more used qualities surviving (being immediately available for use) and less used ones being relegated to backwaters of the system (effectively dying, albeit with the possibility of resurrection if added again). This allowed for such metadata to provide a mirror of the values that mattered most within a given community or network, rather than being imposed uniformly on everyone, and for those values to evolve as the community itself evolved. While I appreciate the simplicity of Facebook’s interface (CoFIND’s most fatal flaw was always that its interface was far too complex to be usable) I still think that user-created ways of emoting – what I have since called ‘fuzzy tags‘ – lead to much more useful reactions that matter within a given community, especially when users can choose the degree to which a fuzzy tag applies. When CoFIND was used in an educational setting, qualities like ‘good for beginners’, ‘authoritative’, or ‘comprehensive’ tended to emerge – they were pedagogical metadata. When used in other contexts, such as to discover what HCI students considered important in a website, site-ranking qualities like ‘slow’, ‘boring’, ‘artistic’ and ‘informative’ appeared.

Parcellation

One of the things I hate most vehemently about Facebook is that it same-ifies everything: a person in Facebook has a single unchanging (and permanently reified) identity, with a single network, a single facade, a single caricatured way of being in the world, notwithstanding the odd nod to diversity like pages and lists. Facebook’s business model relies on this, because any clustering or parcellation reduces the potential to connect, and connections are everything to Facebook. This makes me highly sceptical of its claimed ‘discovery’ that people are actually separated by only 3.57 degrees rather than six. Given that the system very deliberately drives them to friend as many others as much as possible, on most tenuous grounds of connection, this is hardly surprising. It shows not that previous studies are mistaken but the extent to which Facebook has manipulated human networks for profit. Apart from evolving to fit a single community, another of the things CoFIND did was to deliberately parcellate the environment, allowing different sets of values to evolve in different contexts. What is ‘good’ in the context of learning to read is not likely to be ‘good’ in the context of learning geometry, so different topics each evolved a (largely) separate set of qualities. This might not have been the best way to drive the growth of large networks, but it was a much better way to enable the self-organized emergence of meaningful communities. It also allowed individuals to express and embrace different facets of themselves, which in turn made it easy to accommodate changing needs and interests: essential in the context of learning, which is (if nothing else) about change.

You can read about the tortuous process of CoFIND’s development and the thinking behind it in my PhD thesis. I continued to develop CoFIND into the mid 2000s but, though the final version was a bit more usable and scalable (I rewrote it in PHP and changed a lot of the mechanisms, simplifying a fair number of things, including losing the fuzzy ratings) I’m still most fond of the final version that is described in the thesis.

Address of the bookmark: http://www.huffingtonpost.com/entry/facebook-reactions-update_us_56ccb128e4b0ec6725e42861?ir=Weird+News&section=us_weird-news&utm_hp_ref=weird-news

Interesting reflections from librarian Barbara Fister on Twitter’s precarious position, turning a ‘mere’ $191m profit on 300m users and not growing fast enough to assure survival. Turning away from the customer-as-product model, she instead makes a case for small, vertical market, paid-for social (but not too social) services, like Pinboard (tagline: ‘social bookmarking for introverts’) and LibraryThing (“MySpace for bookworms”).

I don’t see these as any more viable than Twitter. If successful, they will be purchased by one of the big few (giving the predator access to my data and social connections) or, if unsuccessful, they will eat my data and my social connections made with them. If they weather all that, the chances of them continuing to grow to meet my ever changing demands are minimal. Vanishingly few will continue to meet my needs for the foreseeable future and it would be foolhardy to bet money that any will survive indefinitely.

And indefinite survival is what is needed, not of the service itself but of the data, processes and social connections that support those data. It is bad enough having elderly files on my own computer that I cannot access at all thanks to proprietary formats. Having such data on a cloud service I may not even be able to access next week is much worse. And, of course, for a social system it is not just about my data but about the network with other people that, when the service dies or I wish to leave it, will be lost.  It’s better to be more of a customer and less of a product, but the endgame is the same either way. Cloud services are susceptible to a thousand and one woes, including unwanted service changes, renogatiated service contracts (seldom beneficial to the customer, once the data are locked in), acquisition, disappearance, failure to grow when needed, and a host of other things beyond my control. The proprietary, locked-in cloud is not the way to go, whether ‘free’ or directly paid-for. It gives the illusion of being open while actually being closed. We need open, portable, distributable and distributed standards for all of this: RSS, OPML, OpenSocial, trackbacks, pingbacks, WebMention and so on. And we need the ability to create, change, move and develop virtual spaces that belong to us, not to a service provider. This is why systems like Known, Elgg and WordPress (with appropriate plugins to support federation) are so important. I find it very encouraging that WordPress (open source and hosted versions) continues to grow and to dominate the social media landscape, powering over 26% of the entire Web. It makes usage of the likes of Facebook, Twitter and YouTube seem like a rounding error, and it is just one of many social systems owned by those that use them.

Address of the bookmark: https://www.insidehighered.com/blogs/library-babel-fish/when-300-million-active-users-isnt-enough

Compelling argument, 10 years old now, that Metcalfe’s Law and Reed’s Law are wrong, and that the correct value for a network should be n log (n). The reasoning is good: the problem with Metcalfe’s and Reed’s laws is that not all nodes in a network are equal. An analogy is made with Zipf’s Law (“if we order some large collection by size or popularity, the second element in the collection will be about half the measure of the first one, the third one will be about one-third the measure of the first one, and so on”) which reflects the uneven distribution of value in a network.

This makes sense to me, but could be taken further. It seems to me that there is no such thing as an ‘average’ network, so we must always examine the actual patterns in any given network to see what value individuals add, and we must always be prepared for some serious outliers that can greatly affect the overall network. If, say, a prime minister or president started to use the Landing, the effect would be quite spectacular (and likely catastrophic, for all sorts of technical and non-technical reasons). There are great risks in averaging things out and looking for statistical effects when observing any human system.

Address of the bookmark: http://spectrum.ieee.org/computing/networks/metcalfes-law-is-wrong

Thanks to Stu Berry for pointing me to this. A fascinating interview, the headline of which doesn’t even begin to characterize the rich range of issues covered, most of which relate to economic, political and social concerns far beyond those of social media. It is very enjoyable and full of wise insights. Bauman’s only actual comments on social media are left right to the end and occur in a single reply:

“The question of identity has changed from being something you are born with to a task: you have to create your own community. But communities aren’t created, and you either have one or you don’t. What the social networks can create is a substitute. The difference between a community and a network is that you belong to a community, but a network belongs to you. You feel in control. You can add friends if you wish, you can delete them if you wish. You are in control of the important people to whom you relate. People feel a little better as a result, because loneliness, abandonment, is the great fear in our individualist age. But it’s so easy to add or remove friends on the internet that people fail to learn the real social skills, which you need when you go to the street, when you go to your workplace, where you find lots of people who you need to enter into sensible interaction with. Pope Francis, who is a great man, gave his first interview after being elected to Eugenio Scalfari, an Italian journalist who is also a self-proclaimed atheist. It was a sign: real dialogue isn’t about talking to people who believe the same things as you. Social media don’t teach us to dialogue because it is so easy to avoid controversy… But most people use social media not to unite, not to open their horizons wider, but on the contrary, to cut themselves a comfort zone where the only sounds they hear are the echoes of their own voice, where the only things they see are the reflections of their own face. Social media are very useful, they provide pleasure, but they are a trap.“

This is a very eloquent and succinct expression of concerns others, like Sherry Turkle, Andrew Keen, Eli Pariser, Tara Brabazon and many more have voiced about social media. I think it is important to have these discussions and to observe what is lost as well as large-scale systemic effects, and this captures the essences of many of those themes very nicely. But it is (necessarily due to its brevity) a distorted caricature that leaves much unsaid. For instance, the question of identity has not changed at all. What we do now have are different ways of playing with identity in addition to what we have always had. We are not seeing a change to everything, nor even a change to individuals, but an increase in the adjacent possible.

Networks and communities

I very much like the phrase “The difference between a community and a network is that you belong to a community, but a network belongs to you” which neatly expresses Wellman’s notion of networked individualism and is a nice characterization of the central difference between groups and networks.

This is, though, a simplified delineation of network and community, because almost all of us are and always have been members of many overlapping communities. And, of course, as Wellman has shown, we do not ever have to choose between one and the other. We constantly move between different networks and communities. Such things can operate simultaneously, sometimes literally – it is unusual not to be at an event with a group of people, especially but by no means exclusively those under 40, where at least one person is not instagramming, facebooking, or tweeting it, extending its meaning and value beyond the collocated community. There is certainly a case to be made that the event itself is thus devalued: it is without doubt affected by this extension, and it is not always in a good way. I have seen whole tables in bars where everyone sitting at them is looking at a cellphone, not at those around them, and I don’t think that is good. But I have also seen tables of people not talking at all without cellphones, and the simple fact that they are together, whether talking or not, is significant and meaningful. The fascination with virtual networks mediated through cellular devices is not the end of this. It is a passing phase that is worthy of reflection and only part of a much richer evolving tapestry. It is related to an older phenomenon of recording an event with a camera. The photographer becomes not a participant but an archivist, and changes the behaviours of other people at the event by making them conscious of themselves and of the event as an historical object. It does raise questions and concerns, but it is part of an evolutionary process that has not even begun to have played out yet.

The first part of Bauman’s response is a little facetiously treating the word ‘friend’ in social networks as having the same connotation as it has in real life. I too hate the devaluation of the term and the ugly cynicism with which Zuckerberg chose it to manipulate the emotions of Facebook members (so hard to explicitly say that someone asking to be your ‘friend’ is not a friend at all), but people with hundreds of ‘Facebook Friends’ seldom if ever believe these are actual friends – if they do, it’s a clinical condition that probably needs treatment.

Doing things together vs talking about it

Bauman’s answer does speak to a concern, not explicitly voiced but I think at the heart of his and others’ concerns, that we are replacing shared practice, purpose and communal activity with dialogue. It matters a lot that people do things together and share the same social, physical or virtual context when they do so. That shared practice or activity – whether it be doing a job, watching a movie, eating together, learning something, creating something, drinking together or whatever – is normally (but not always) lost in social media, which are often concerned with talking about such things rather than doing them together. This can blind those that view it as outsiders to the rich complexity of what is really going on within overlapping communities and networks of participants. They see individuals leading separate lives and talking about them, which would, indeed, be extremely shallowing and alienating if it were all that they did. But, except in extreme and worrisome cases, that is simply not the case. It may be a worry that many people are leading second-hand lives, talking about people talking about people, though this is not a new problem with social media, but an unfortunate side-effect of mass media (one of many). We have lived with problems like the cult of celebrity for a very long time. At least social media provide a greater chance to talk about the problem!

Filter bubbles and echo chambers

The difference between doing things together and talking about doing things together also speaks a little to the second half of the response, which is about fllter bubbles and echo chambers. When we do things together in the world, we constantly negotiate and jostle for meaning, action and purpose. Just talking about it is not the same. When we do things together, there is inevitably conflict, albeit seldom great enough to barely even notice – when we adjust our walking pace to walk together, when we feel we must show interest in things that bore us, when we choose a bottle of wine, etc. There is also delight and serendipity. Doing things together is what social life is all about: talking about it, reflecting and reminiscing, is largely a binder, a reinforcer and a connector that helps us to make shared sense and meaning out of that. When we do things together we cannot shut out or ignore those that we do them with. Popular social networking systems seldom replicate this doing-together, but many social media do: most obviously social games, but also a wide range of collaborative tools, from shared calendars to project management tools. Social media are very diverse and are usually very soft, so can play many roles. Email, as a classic example, can support almost any level of engagement, community or practice. My wife and I used to watch movies together via Skype when we were apart. To treat all this diversity as though it were Facebook is silly, and even Facebook has a very wide range of tools, purposes, uses and (yes) even communities.

There is a real and worrisome sense that filter bubbles and echo chambers are dangerous, albeit that it has ever been so. In the olden days we built those bubbles through our choice of friends, newspapers, and TV viewing and, in the mass media, editors performed the filtering for us. In the olden days, I used to just ignore sections of newspapers that addressed things that did not interest me. Now, we have a much richer potential range of things to choose from, but the bubbles are built by algorithms more often than human editors or, as in collaborative filters, through cyborg hybrids of machine and people. We do not just select what we want to see but, once we have selected it, a system performs further selection for us, often based on a coarse user model designed by a programmer (the failures of which are actually sometimes a good thing, because their mistakes show us things we might otherwise ignore or never even see). Furthermore, given the large amount of stuff out in the stuff swamp (Walt Crawford’s delightful term) and the incredibly large range of inhabitants of it, it is easy to find what seem like many people who share the craziest of views, from creationists and climate-change deniers to flat earthers and alien conspiracy believers, so it is easier to find support for niche beliefs that separate rather than connect us. There is a home for cliques and cults like there has never been before, and tribal feelings have seldom been so visible or so strong.

Luckily, though, diversity is never far from view unlike, for quite a lot of the world, in real life, where our jobs and locales seldom expose us to much that is unfamiliar and where norms are constantly and relentlessly reinforced, especially those of us that do not live centrally in cities or large towns. Most of us are not part of a single network, but are members of many overlapping communities, and many networks connected by diverse and different kinds of connection, virtual and physical. Few of us limit our engagement to a single tool, site or system and, by engaging beyond our geolocated communities, we bring enriching new perspectives to them, and return the distinctiveness of our isolated communities to those networks. Furthermore, as Terry Anderson and I have noted, a great deal of the Internet is about neither communities (groups) nor networks, but about sets. For instance, many of us view a lot of individually or group  or crowd-curated content, from Best of Reddit to our local newspaper. These don’t burst our filter bubbles but they do bring in a lot of serendipity and fuel our networks and communities with an ever-burgeoning range of diverse views. This provides a great many counterbalances to the problems of echo chambers and filter bubbles. There is a lot of noise out there, clamouring to be heard.

So, I don’t think Bauman is wrong. The concerns that he caricatures are very real. I just think that it is very much more interesting and complicated, with positive and negative effects, than a concise summary of concerns can hope to reveal. I suspect he might agree.

Address of the bookmark: http://elpais.com/elpais/2016/01/19/inenglish/1453208692_424660.html

Space is the Machine, a book by Bill Hillier, is available online for free, and is also back in print again after too long an absence. Around 15 or so years ago this book changed how I see the world. As my own well-thumbed paper copy has suffered a lot over the years, and is a very large, heavy object that attracts a lot of dust and not much reading, it is delightful to be able to dip into the pristine electronic version and again be inspired.

This site has each chapter individually downloadable. A full 368-page copy is available at http://discovery.ucl.ac.uk/3881/

The book is as much a work of philosophy as it is of architecture and urban planning (its main subject matter). It incorporates insights from sociology, psychology, anthropology, network theory, linguistics, complexity theory, distributed cognition, systems theory, aesthetics, engineering, ecology, collective intelligence, topology, emergence and more. The ideas it embodies have far broader potential applications than the built environment, including to ways we think about the purpose and practice of education, as well as to more obviously related things like the design of online social applications. In brief, it provides a way of understanding complex human systems and environments as interconnected configurations of structure, objects, time, and movement, in constant dynamic and emergent interplay with abstract, social and psychological phenomena. There are strong echoes of Jane Jacobs (uncited) and Christopher Alexander (cited) in all of this, but it goes farther up and farther in.

I don’t know whether the book and the theories of space syntax it describes impress most architects and urban planners. As I am neither, that’s not the point for me. Whether all the arguments and conclusions make sense in its intended context or not (and some are a bit suspect, even to an outsider like me) this book repeatedly makes strikingly novel connections between diverse and otherwise incommensurate fields, and it constantly provides new perspectives that make the familiar strange and fascinating. It is inspiring stuff.

Address of the bookmark: http://spaceisthemachine.com/

An interesting side-effect of the way Facebook relentlessly and amorally drives the growth of its network no matter what the costs: stupidity thrives at the expense of useful knowledge.

This study looks at how information and misinformation spread in a Facebook network, finding that the latter has way more long-term staying power and thus, thanks to EdgeRank and the reification of communication, continues to spread and grow while more ephemeral factual pieces of news disappear from the stream. I suspect this is because actual news has a sell-by date so people move on to the next news. Misinformation of the sort studied (conspiracy theories, etc) has a more timeless and mythic quality that is only loosely connected with facts or events, but it has a high emotional impact and is innately interesting (if true, the world would be a much more surprising place), so it can persist without becoming any more or less relevant. It doesn’t have to spread fast nor even garner much interest at first, because it persists in the network. All it needs to do is wait around for a while – the Matthew Effect and Facebook’s algorithms see to the rest.

There is not much difference between interest in scientific and anti-scientific articles at the start. There is a wave of activity for the first 120 minutes after posting, then a second one 20 hours later (a common pattern). But then the fun starts…

“It’s over the long term that serious differences were observed. While the science news had a relatively short tail, petering out quickly, conspiracy theories tended to grow momentum more slowly, but have a much longer tail. They stick around for a longer period of time, meaning they can reach far more people.

Then there’s another problem with the way Facebook works – the much-discussed echo-chamber effect. This effect is far more active in Facebook than in other networks, with algorithms favouring content from people and groups you regularly interact with. So if you share, Like or even click on conspiracy theories a lot, you’re more likely to be shown them in future, reinforcing the misinformation, rather than challenging it.”

Address of the bookmark: http://www.alphr.com/science/1002377/study-shows-facebook-spreads-nonsense-more-effectively-than-fact

Fascinating article from 2013 on an experiment on a live website in which the experimenters manipulated rating behaviour by giving an early upvote or downvote. An early upvote had a very large influence on future voting, increasing the chances by nearly a third that a randomly chosen piece of content would gain more upvotes in future, with final ratings increased by 25% on average. Interestingly, downvotes did not have the same effect, making very little overall difference. Topics and prior relationships made some difference.

This accords closely with many similar studies and experiments, including a social navigation study I performed about a decade ago, involving clicking on a treasure map, the twist being that participants had to try to guess where, on average, most other people would click. About half the subjects could see where others had already clicked, the about half could not. The participants were aware that the average was taken from those that could not see where others had clicked. The click patterns of each set were radically different…

On closer analysis, of those that could see where others had clicked, around a third of the subjects followed what others had done (as this recent experiment suggests), around a third followed a similar pattern to the ‘blind’ partipants, and around a third actively chose an option because others had not done so – on the face of it this latter behaviour was a bit bizarre, given the conditions of the contest, though it is quite likely that they were assuming just such a bias would occur and acting accordingly.

One thing that might be useful, though very difficult, would be to try to weed out the herd followers and downgrade their ratings. StackExchange tries to do something like this by giving more weight to those that have shown expertise in the past, but it has not fully sorted out the problem of the super-influential that have a lot of good karma as a result of gaming the system, as well as the networks that form within it leading to bias (a problem shared by the less-sophisticated but also quite effective Reddit). At the very least, it might be helpful to introduce a delay to feedback being shown until a certain amount of time has passed or a threshold has been reached.

One thing is certain, though: simple aggregated ratings that are fed back to prospective raters (including those voting in elections) are almost purpose-built to make stupid mobs. As several people have shown, including Surowiecki and Page, crowds are normally only wise when they do not know what the rest of the crowd is thinking. 

ABSTRACT

Our society is increasingly relying on the digitized, aggregated opinions of others to make decisions. We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates distorts decision-making. Prior ratings created significant bias in individual rating behavior, and positive and negative social influences created asymmetric herding effects. Whereas negative social influence inspired users to correct manipulated ratings, positive social influence increased the likelihood of positive ratings by 32% and created accumulating positive herding that increased final ratings by 25% on average. This positive herding was topic-dependent and affected by whether individuals were viewing the opinions of friends or enemies. A mixture of changing opinion and greater turnout under both manipulations together with a natural tendency to up-vote on the site combined to create the herding effects. Such findings will help interpret collective judgment accurately and avoid social influence bias in collective intelligence in the future.

Address of the bookmark: http://www.sciencemag.org/content/341/6146/647.full