In previous posts, especially in those related to content mapping, I frequently referred to collective actions and efforts in describing certain concepts, but never elaborated on the exact meaning of these terms. One could think that collectivity and collaboration are identical (they often are mentioned in the same context) as both have something to do with individuals working together. In fact, I find it important to highlight their differences for I expect collectivity to play as vital a role in Web 3.0 as collaboration did in Web 2.0.
As already understood from popular Web 2.0 applications such as Wikipedia, Google Docs, or WordPress, we define collaboration as sharing workload in a group of individuals who engage in a complex task, working towards a common goal in a managed fashion, and are conscious of the process’ details all the way.
As the number of participants grow however, it becomes apparent that collaboration is not scalable beyond a certain level while remaining faithful to the definition outlined above. Although there is such a thing as large-scale collaboration, what that covers is lots of people having the possibility of contribution but in reality only a few doing so. Mass collaboration goes further by blurring the definition of collaboration so much that it practically becomes just another expression for collectivity.
And when I speak of collectivity, I think of a crowd performing a simple, uncoordinated task where participants don’t have to be aware of their involvement in the process while contributing. The outcome of a collective action is merely a statistical aggregation of individual results.
Collaboration and collectivity operate in different realms. Collaboration can be thought of as an incremental process (linear) while collectivity is more similar to voting (parallel). On the figure below, arrows represent the timeline of sub-tasks performed by participants.
Suppose a sub-task like that was the creation or modification of a Wikipedia entry. In this case collaboration proves more effective, as it offers a higher chance of eliminating factual errors during the process, while a collective approach would surely preserve all of them (and offer the one with the fewest). The semantic complexity of a document does not fit the more or less hit-and-miss approach of collectivity.
However, if we decrease the complexity of the content, say, to one sentence, the probability of individual solutions being as ‘good’ as products of collaboration is expected to be equal. Collective approaches therefore suit low-complexity content better.
The synaptic web
What content is of lower complexity than connections within a content network? Different relations such as identity, generalization, abstraction, response or ‘part-of’ require no more than a yes-no answer. Collectivity is cut out exactly for this kind of tasks.
As the creators of the synaptic web concept put it,
With the advent of the real-time web, however, increasingly effective publishing, sharing and engagement tools are making it easier to find connections between nodes in near-real time by observing human gestures at scale, rather than relying on machine classification.
Hence the synaptic web calls for collectivity. What we need now is more applications that make use of it.
- Just one day before my post, @wikinihiltres posted an article comparing the efficiency of collective and collaborative approaches to content production through the examples of Wikipedia and Wikinews, concluding that “the balance that ought to be sought is one that continues to accept the powerful aggregative influence, but that greatly promotes collaboration where possible, since collaboration most reliably produces good results”.