London Knowledge Lab: Social Software

June 15, 2006

Notes on Ramos et al’s Swarm intelligence

Filed under: Readings, Tagging — yishaym @ 11:34 am

I find this week's paper interestingly related to Jaron Lanier's essay (for which we should thank Phillip). I take several ideas from Ramos et al. First, the basic phenomena of distributed intelligence, whether distribution is among organisms or neurons. As they phrase is - 

"The answer is somewhere spread in the dynamics and interactions among several units of the system, not on the units itself." (p 4)

Then comes the question of where does intelligence emerge. As Lanier's eloquently observers, the hive mind can be as stupid as the most stupid individual. Ramos et al suggest that what is needed is a very delicate balance of positive and negative feedback, Stigmergic memory and evaporation (forgetfulness), with the right dose of random behaviour. Where is that balance?

Intelligence lives on the edge of chaos.

Last, I find the notion of Stigmergy fascinating. Wikipedia defines it (today) as: 

"Stigmergy is a method of communication in emergent systems in which the individual parts of the system communicate with one another by modifying their local environment. Stigmergy was first observed in nature – ants communicate to one another by laying down pheromones along their trails, so where ants go within and around their ant colony is a stigmergic system. Similar phenomena are easily seen in many (all?) eusocial creatures, such as termites, who use pheromones to build their very complex nests by following a simple decentralized rule set. Each insect scoops up a 'mudball' or similar material from its environment, invests the ball with pheromones, and deposits it on the ground. Termites are attracted to their nestmates' pheromones and are therefore more likely to drop their own mudballs near their neighbors'. Over time this leads to the construction of pillars, arches, tunnels and chambers."

Are Tags and trackbacks our pheromone trails?

May 30, 2006

Collective Intelligence: some theories

Filed under: Blog, Learning, Memory, Readings, Reflections, Research, Review, Uncategorized — giota @ 5:08 pm

This week I will present a brief overview of Pierre Levy's theories on collective intelligence.

One of the most influential theorists of Cyberculture, Pierre Lévy offers a metaphorical conceptualization and posthumanistist theorizing of cyberspace to argue for a new relationship between technology and knowledge. His view on collective intelligence allows the cultivation of a mutually developed and enhanced knowledge space through social interaction and associatiative cognitive exchanges. Lévy’s ‘information utopia’ can be nspiring for grasping the cultural ethic of open source movements and social software we have been discussing in the seminars. But as much as such approaches enlighten some elements of the cultural interfaces of the Web, they also obscure, I would like to argue, the clear relationship between the Web, digital knowledge forms and the rest of the industrial society. I will try to combine some of our reflections on the definition and classification of social software with some of my research findings from online encyclopaedias (including wikipedia).

May 26, 2006

Mika’s Ontologies

Filed under: Course resources, Learning, Readings, Reflections, Semantics — wilmaclark @ 9:31 pm

I finally managed to grab some time to read Mika’s article and found it very interesting – not in a mathematical sense, but maybe in more of a ’social science’ sense.

I liked the notion of a tripartite model of actors-concepts-instances. This move from the bipartite model (concept-social) to include the ternary element of ‘actor’ or ‘agency’ is interesting. It kind of mirrors something I’ve come across in my own research into cultural semiotics where, in moving from notions of binary opposition in meaning generation, the idea of a ternary system is introduced, the third element being the process of interaction… whether social or otherwise. It seems to me that in a triangulation of elements, a certain notion of balance emerges – perhaps that’s because the ‘thirdspace’ situates or anchors the propositional knowledge? So, in this way… the introduction of the ‘actor’ by Mika lends itself to his later elaboration of ’semantic identity’ being something that emerges from a community network or collaborative group, for example in the production of ‘tags’.

The functionality of a ‘group’, as it were, automatically ‘frames’ their thinking (tagging) and collective memory (Mika’s ‘agreed upon terms’) and this, of itself, helps to categorise the apparently ‘loosely’ defined tags generated by the members of the community. So that, if you like, even though each individual makes an individual choice as to which tags to use, the tags are used within a ‘visualised set’ belonging to the group (Mika’s ‘concensus’), which makes them less problematical as identifiers because the element of randomness is thus lessened.

I was intrigued by Mika’s raising of temporality as a problem in concept definition… (his ‘ontology drift’) but, for myself, saw this as a natural part of the evolving semantic map and not as problematic as he suggests as, surely, there are causal links which tie new concepts back to old ones, even as communities change and evolve? Knowledge may be ‘codified’ as Mika suggests, but must codification always signify something which is fixed?

I liked Mika’s vision of a dynamic ontology as a ‘community of self-organising, autonomous, networked and localized agents… establishing connections and negotiating meaning only when it becomes necessary for co-operation’. He suggests that there is a lack of an abstract model for such a system but, actually, it seems to me that this ties into Yuri Lotman’s concept of semiosphere (forgive me for plugging my own research interests here). That said, Lotman’s semiosphere is demarcated as an abstract model for meaning making/meaning generation, whereas Mika’s interests seem to lie in connectivity of concepts for meaning making. Both, however, envisage meaning made on multiple levels and as multilayered.

Mika points out the lack of ‘one-to-one correspondence’ in keywords generated by individuals when tagging… however, although not explicitly stated… the notion of ‘many-to-many correspondence’ seems somehow appealing in the context of tagging and folksonomies.

I really liked his explanation of the relationship between user, object and concept and the notion of ternary associations. Forgetting the maths and the fancy language – lovely word ‘hypergraph’ but don’t they block the way sometimes? and just fixing on the concepts, I liked the idea that the combination of these three produces a ‘higher level’ concept that is accessible in different ways, so that, even where tags are non-identical, some overlap in conceptual framing at this ‘higher level’ may bring them together into one category – so, where two might not meet, three have the potential to do so… (thanks for the nice graphs, Yish). I did chuckle a little at the understatement:

Tripartite graphs and hyperedges are rather cumbersome to understand and work with. (Uhuh!)

How I summarised the rest… take two people who share an object, expressing its value with different tags… the object’s defining potential is multiplied by two… and so on. For me, I ignored the hyperedges and affiliations and instead pictured an ever-growing spirograph, growing rapidly more dense at different nodes around a central point (actor or object) – equivalent to the weighting/filtering properties of the ‘affiliation network’ – well, it kind of works for me and makes for interesting reflection. The idea of ‘overlap’ in conceptual framing generating an emerging semantic network seems eminently feasilbe (and somehow sensible) to me.

Skipping along, some other things I picked up on and which interested me:

- the notion of observing tagging behaviour to determine the kinds of meanings they generate – whether collectively or individually
- reflecting on the idea of a ‘collective mind set’
- the ‘well-known law of community formation’

I really like this: “interaction creates similarity, while similarity creates interaction” – I think it’s a nice phrase to link to the whole idea of social networking, although I’m curious as to the scope of the notion of ’similarity’ and what this might engender in terms of collaborative or communal interactions. It also kind of brings up the question of ‘the chicken or the egg’ and which comes first. Something worth thinking on, just the same.

Some quick notes without too much reflection (from later sections):

  • social bookmarking: link, describe, tag (keyword) and share
  • bookmarks: searchable, affiliated, associated, temporally situated
  • issues: synonyms, ambiguity, generalisation
  • community: core interests, clustering, evolving, correlations
  • folksonomy: tagging, keyword associations, community ontologies
  • Finally, the comparison of ‘object’ (say, search engine) and ‘actor’ in terms of effectiveness as meaning negotiators had me thinking (and I’m still thinking)… when I read this:

    Overlapping communities turn out to be a stronger link than overlapping sets of web pages. A possible explanation is that even after including the disambiguating term in the query, the search engine still suffers from knowing too much, blurring away community-specific interpretation.

    The idea of a search engine ‘knowing too much’ made me smile… sure had that ‘glut’ problem myself. Quite apart from the fact that a community has more consciousness (by virtue of its members) – the idea of the ‘overlap’ between communities generation meaning in and of itself is an interesting one. I’m wondering about the point of intersection and the ‘zone’ where meaning is made in such a case… which kind of ties in with Lotman’s notion of ‘explosion’ and the idea that where two apparently correlating actors and concepts interact… meaning is self-generating at some level but not necessarily immediately perceived… I’m wondering whether Mika’s interpretation of the interpretative impact of overlapping communities is similar to Lotman.

    May 18, 2006

    I’m a social scientist. get me out of here!

    Filed under: Readings, Reflections, Social-Bookmarking, Tagging — yishaym @ 2:11 am

    I suspect some of may have found the use of matrix arithmetic and graph theory in this week's paper a bit overwhelming. I still think its a paper worth reading. First, its good to know that there's more to Matrixes than Morpheus. Second, its interesting to see how people are trying to fit formal models to intuitions.

    So lets focus on the intuitions. As a first aid measure, try applying masking tape (preferably purple) to every paragraph that has squigly brackets, and see how it's already become more friendly.

    Now lets talk about hypergraphs. This here picture shows Actors (AKA users or plain people), instances (AKA resources, documents or web pages) and concepts (AKA words, tags, categories).

    When a person tags a page, she creates a triparty relationship between person, tag and page. Mika calls this a hyperedge. I draw a triangle.

    When many people do the same to many pages with many tags, you get what Mika calls a hypergraph, and would probably be refered to in plain English as a 'pretty big mess' (not to be confused with a mesh).

    So what do mathematicians do with big messy problems? They find a way to break them down to many small less messy problems. In the case at hand, we do so by looking only at one type of connection at a time, say the dotted lines (tag – page) and measuring it along another (say number of persons). So, we get nice and simple graphs that connect only tags (concepts) by counting the number of things they have in common. For example, if a lot of pages are tagged 'sex' and 'table' we induce there's a semantic connection between the two.

    As Mika explains:

    In words, the bipartite graph AC links the persons to the concepts that they have used for tagging at least one object. Each link is weighted by the number oftimes the person has used that concept as a tag. This kind of graph is known in the social network analysis literature as an afiliation network [7], linking people to affliations with weights corresponding to the strength of the afiliation. An afiliation network can be used to generate two simple, weighted graphs (onemodenetworks) showing the similarities between actors and events, respectively. (At this point it is recommended to dichotomize the graph by applying somethreshold.)

    In summary, the AC graph, the a±liation network of people and concepts can be folded into two graphs: a social network of users based on overlappingsets of objects and a lightweight ontology of concepts based on overlapping setsof communities. Thus in this simple model, social networks and semantics are just flip-sides of the same coin: the original bipartite graph contains all theinformation to generate these networks, while it it not possible to re-generatethe original graph from them.

    Mika compares two ontologies (= networks of concepts) derived in this process. One links concepts by the number of people who use them together, the other by the number of pages they are mutualy associated with. It turns out that looking at peopls (communities) is a better way to discover semantic relationships than looking at objects. In other words, the same resource means different things to different people, but people in the same community share a common set of meanings.

    Well, I think Wenger and Lave would be pleased to hear this.

    But there are other networks that can be derived. By fixing the concepts, we can plot the potential social relationships, common interests or implicit communities. Which brings us back to Lyndsay's point. If a tagging system wants to survive its own growth, perhaps it should make these networks explict. For example, identify clusters, show them to me, and show prioretize resources tagged by people who share my social cluster.

    May 17, 2006

    Any volunteers?

    Filed under: Readings, Research, Social-Bookmarking, Wikis — yishaym @ 11:28 am

    I've stumbled upon Sebastian Schaffert's work on 'semantic wikis'. Looks interesting, but I don't have time to read the papers today. I was wondering if anyone has heard about this stuff before, or if someone wants to have a closer look and share some thoughts.

    If you do read a paper or two, please try to enter a reference in Bibsonomy, or any equivalent service that exports BibTex. Just to save the others the trouble of listing the bibliographic details.

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