Sincrético

My relatively short research about different categories of knowledge has led to me to conclude that there are only two kinds: scientific and non-scientific knowledge. The former is objective and considered as true knowledge, the latter is everything else: everyday knowledge, narrative, culture, personal knowledge, ideology, common sense, religion, and so on. Is a cultural product such as music a piece of objective knowledge because it’s recorded? Is cultural knowledge, in the form of music able to grow? When music is recorded, its growth is put to rest, momentarily or indefinitely.

I think that’s the case when music is protected by more stringent copyright systems. Although it’s existence is more stable, it’s cultural growth is certainly impaired. Because some of these systems are so draconian, the products which they govern seem to reach a final stage. Naturally, there is the central aspect of which business model musicians should take; everyone has to make a living. To that David Byrne wrote an interesting article about it on Wired.

But that’s not the concern of my research. My interest is to find out whether the communicative strategies of the Web 2.0, such as podcasts, blogs, social networks and collaborative spaces, are able to  create a growth in cultural and non-scientific knowledge. Dissemination of information does not necessarily entail that what is communicated will generate new knowledge. What will certainly happen is a growth of the social aggregate of knowledge, that is, more people will know.

By using alternative licenses, such as those offered by Creative Commons, we may able to ascertain that growth will be maintained. The idea is very obvious and simple. An artist records a song and makes it available on his website under a CC license. Someone downloads it, changes it, remixes it, uses it as a sample or whatnot, and also puts it on her website, following a similar CC scheme. Given that licensing and all the attributions foreseen are respected, the process is continuous and new cultural knowledge is generated. In the case of traditional copyrights, the possibility of creating new cultural knowledge is as good as none, finito.

It’s been hard to find time to write about anything nowadays…

Today I’m using the blog truly as a way of organizing my thoughts. I am having a bit of a hassle to organize my notes about networks and the spread of information. There are a couple of dimensions to cover. First, the technical aspects starting with graphs and their evolution to the modern manifestations of small-world networks and its subsequent variations such as — if I am correct — scale-free networks, including their inner structure, the connectedness of their nodes, their order and randomness and other technicalities.

Secondly, when specifically talking about social networks, there are issues such as the actors within them and the roles they play such as hubs and authorities, as well as the so-called “influentials” and their apparently marginal advantage in comparison to “normal” nodes in their capacity to spread information more efficiently (cf. Watts). One must not oversee the functions of strong and weak ties (cf. Granovetter), the former being part of tightly knit clusters formed of intimate connections and the latter functioning as bridges between different clusters on a network. Weak ties, according to Granovetter’s highly influential theory (1973), play an important role as bridges between different communities. Other social roles must be also taken in consideration, such as those of opinion leaders (Katz, Lazarsfeld 1955), innovators and early adopters in the diffusion of innovations (Rogers 2003) and more popular incarnations of “influentials” like those described by Gladwell (2000), among others.

Thirdly, with the social roles accounted for, we must, or I must :-), consider the spread of information and the dissemination of knowledge across networks, taking in considerations the several concepts and models that have been established in the analysis of social networks and in the “new” science of networks (Watts 2004). There are theories such as the SIR model (Susceptible, Infected, Recovered) which look at the spread of information from an epidemiological perspective with variants that take in consideration the “resistance” of nodes to contagion (thresholds). Other approaches include information cascades, percolation theories, the diffusion of innovation model of Rogers, among others. But their all share a similar aspect, that nodes can in way influence each other, depending on their ability to convince their neighborhood and the latter’s resistance these ideas, and also how connected nodes are to one another. If nodes are too tightly connected, cascades stay local, if they are too loosely connected to random parts of the networks cascades may disperse; there should be a compromise between looseness and density. Virtue lies in the mean as our good friend Aristotle would already say back in the day.

Anyway, this post has got much bigger than I expected. It however helped me in putting a mess to my thoughts. I’m starting to appreciate this blog thing… that is, if one is able to find the time to do it

Work referenced in this post:

Gladwell, M. (2000). The Tipping Point: How Little Things Can Make a Big Difference. New York: Little, Brown and Company.

Granovetter, M. (1973). The Strength of Weak Ties. American Journal of Sociology , 78 (6), 1360.

Rogers, E. (2003). Diffusion of Innovations. Simon and Schuster.

Thomson, J. (1955). The Nicomachean Ethics. Penguin Books: London.

WATTS, D. (2004). The New science of networks. Annual review of sociology , 30 ,
243–270.

I’ve been researching for the past weeks whether knowledge is able to grow within social contexts. Throughout the literature that I came across, there is a stark distinction between scientific and non-scientific knowledge. Philosophers of science such as Popper don’t even consider the product of the “episteme” to be knowledge at all, and it has mainly to do with the question of truth. That’s a difficult and controversial topic, but for the purpose of my research I assume that any form of knowledge, scientific or not, must be assumed to bear, at least in social contexts, a shared agreement as to what it is to be “true”. I will no longer differentiate scientific and non-scientific knowledge, and will call it just knowledge.

So, assuming that knowledge to be called as such must be true, is it possible to maintain, and to measure, that it can grow, even if it can’t be fully objectified? Let’s consider for example culture, which I consider to be a subset of knowledge. Almost everything we do is somehow strongly influenced by culture, our surroundings, our previous knowledge of objects and concepts, in other words, our “operational” knowledge, which shapes our actions and tastes. As I am writing this, I am drawing concepts from past memories, working within a set of rules of communication (the blogosphere) and expecting a certain  way understanding from the part of eventual readers, a shared culture if you will. The very text you are reading is a product of combination of external and internal knowledge and that has gone to a certain cognitive work-through, grounded on mental and cultural processes. Some readers might use some of the ideas found on this text, combine with others and with their own and create other texts, contributing to an chain of narratives that will eventually demarcate the boundaries of one specific subculture.

The growth of this knowledge is almost impossible to objectify. Therefore we must resort to other means such as the understanding of the communication technology with which this knowledge is produced and communicated to attempt to quantify it. Since the internet is inherently “measurable”, with log files, backlinks, trackbacks as well as with other data about the dissemination of information being largely available, at least potentially, we have means to understand this growth. One way is to look at the social structure in which this knowledge exists and try to understand the dynamics and informational flows of this environment. Another is to look at how content is transformed through time, that is, how progress and eventual setbacks happen along the communicative way of knowledge. One thing is tantamount to the growth of knowledge as much as it is a platitude: knowledge only grows when its communicated.

When concepts are put into words, in order to be understood they must be phrased within common language and be meaningful to the participants involved in the communication activity. This is what Habermas calls universal pragmatics, in which he sets forth a set of “validity claims” in order for communication to be productive. So when words, sounds and images are out there, we’re inevitably — as long as we are meaningful — contributing to the growth of knowledge as long as there is at least one receiver of the message. What this receiver ultimately does with message will only contribute to the social aggregate of knowledge as long as its also subsequently communicated.

Naturally, this must be quantified in some manner. Alvin Goldman, a philosopher studying social epistemology, calls these gains in knowledge Veritistic Gains or simply “v-gains”. In order to achieve a higher v-gain, participants with low knowledge must communicate or interact with participants that have a higher knowledge of a specific topic. The highest v-gain possible is when a inquiry is “fully” answered and one moves from a state of non-belief (no knowledge) to full belief (high knowledge). Here we coming back to question of truth again, but as aforementioned I regard knowledge as being true with a certain agreed context (relativism can be discussed later) and moving from no knowledge to high knowledge is no small feat, and it largely relies on communication.

Kind of continuing on the previous post about the creation of new knowledge. Lilia Efimova has wrote some interesting papers on the nature of blogging and it’s relation to knowledge. Although writing from the perspective of knowledge management within organizations, she establishes interesting concepts in which blogging may be useful in one’s stride to organize his or her knowledge. One may use a blog as personal content management system, I certainly have been doing that. Sometimes posts might not even be published, but just the fact that you must put them into readable thoughts, may help you in structuring your ideas for future access.

We can also use this space to create a conversation, which is a way of maintaining knowledge alive for a period of time — as long as the conversation is going on — and a way of polishing your arguments, which in itself may not be considered new knowledge, but as refinements of existing thoughts. You can gain however insights from comments and conversation, assuming that you amass the right audience for your topics. I personally am new to blogging, just about over a month, and the more I write it, it seems, at least, the more comfortable I feel about it. This is also another topic covered in one of her papers. Later I will certainly come back to them in more detail.

If you are interested in insightful research on blogs, here are some of Efimova’s papers on the topic.

• Efimova, L. Blogs: The Stickness Factor. Blogtalk: A European Conference on Blogs. 2003.
• _________. Discovering the iceberg of knowledge: A weblog case. Proceedings of the Fifth Conference on Organisational Knowledge, Learning and Capabilities. 2004
• Efimova, L. and Hendrick, S. and Anjerwierden A. Finding “the life between buildings”: An approach for defining a weblog community.” Internet Research, Volume 6. 2005
• de Moor, A. and Efimova, L. An argumentation analysis of weblog conversations. Proc. LAP 04, New Brunswick. 2004.

Does the Web 2.0 actually increase the stock of knowledge held by those with access to it, or does it maintain the existing level and merely transmits it? Me and my Thesis supervisor, Prof. Paolo Paolini at the University of Lugano, haven’t really arrived yet at any conclusion. I set out to a little investigation on the epistemology of Web 2.0, I found of some papers, not specifically on the topic, but mainly in relation to the creation of new knowledge with the help of new technologies.

Without yet so much theoretical support I risk to say that, perhaps, the increase of knowledge comes through the otherwise non existing connections of different knowledge pools, in other words, through the interconnection of different disciplines, which is made nowadays much easier with the use social technologies, and an exponential augmentation of serendipitous knowledge finding methods, leading to new “open doors”. Today I read Lyotard’s “The Postmodern Condition: A Report on Knowledge“, which has thoughtful and acute insights in this direction. Although written in 1979, some of his predictions were actually spot on, especially related to explosion of “computerization” and the almost ubiquitous access to an overall knowledge “data bank.” It’s cute how old folks talk about technology.

What he has not predicted was that those that would have access to this knowledge would also be able to alter it, mash it, remix it and give their interpretation on it. And also the speed in which information goes through “nodes” (us) today does probably affect the way in which we are able to acquire this knowledge, it is probably more than ever just in a transient state. We might not even acquire it, we are just permeated ad-hoc by it upon need. There is much more to his arguments of course, and it is not about technology, it’s about how people have lost their belief in a grand metanarrative or ideologies, and how this leads into new ways for the legitimation of knowledge. Anyway, it’s a thin — I mean in the number of pages — and thought-provoking read.

Anyway, going back to the beginning question of this post… anybody there knows it?

As I described on part 1, I have been running a little research to verify whether RSS feeds generated by blog and news searches are of any worth. On the following parts I will be presenting the final data, some analysis and conclusions. Please refer to the original post in order for a more detailed explanation of the methodology and its motivations.

Scope

The scope of this research is very narrow and can only be applied for the selected keywords below. Therefore, the results should not be generalized. A more representative research would need a much larger sample of random keywords, possibly in different languages, using different search engines and more rigorous data collection. Nonetheless, the results shed some light on using RSS feeds as an additional way of information gathering, specially in the exploratory phases of a research.

Data collection

As described in the introductory post, I created a series of subscriptions with some keywords for a Google blog and a Google news search. The keywords, based on the title of my master’s thesis “Dissemination of Knowledge and Culture on Web 2.0: a Case for Brazilian Music”, were based on the first part of the title, and used for the different searches in different levels of complexity, as follows:

• “dissemination knowledge culture web 2.0″
• “dissemination knowledge web 2.0″
• “dissemination culture web 2.0″
• “knowledge culture web 2.0″
• “knowledge web 2.0″
• “culture web 2.

I observed each subscription on Google Reader daily, for a 30-day period, from 19 March until 17 April. For each set I considered the following variables:

• Total Feeds: the daily number of feeds for a subscription
• Overrides: how many repeated feeds were found within a subscription or across the whole set
• Preselections: feeds that have been marked (or starred in Google Reader) for further reading
• Primary leads: interesting leads that may serve as a reference derived from a preselection
• Secondary leads: any interesting lead found within a primary lead
• Bookmarks: effective sources found in the chain of leads that are bookmarked and tagged
• New RSS feeds: new rss subscriptions generated as a result of good content found within a blog or site that contains other articles of interest, and may serve as an expanding sourc

Table 1: Consolidated data table for the Google Blog Search (all keywords combined)

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Table 2: Consolidated data table for the Google News Search (all keywords combined)

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I recently stumbled upon the concept of stock and flow of information. In simple words flow is everything that is occurring within a time interval, and stock everything that can be observed statically. For example, RSS feeds and blog entries such as this one are flow, archived blog entries and structured content to be found later such as a Wiki entry are stock. In less prosaic style, flows are the rivers, stocks are the reservoirs.

The terms, which are widely used in economics, business and accounting, are distinguished by their relation to time. Stock variables are measured on a given time, whereas flow are measured within an time interval. The concept was originally devised by system dynamics scientist Jay Forrester, who originally referred to the terms as Level (stock) and Rate (flow). [Wikipedia]

I haven’t been able yet to find any academic studies of stock and flow related to online communication, they are mostly associated to stock markets and system dynamics. CommonCraft has 3-part easy introduction to the topic in relation to the circulation and archival of information on the internet. Although the concept here seems to have been borrowed from other disciplines, it’s relevance is not all too inappropriate.

In the last few days I have gathered some time to read Six Degrees: The Science of a Connected Age from Duncan J. Watts, professor of sociology at the University of Columbia and The Tipping Point: How Little Things Can Make a Big Difference from Malcolm Gladwell, a New Yorker columnist and writer. In an earlier post, based on a article found a Fast Company, I have opposed the two, saying they were representing two different currents of thoughts in relation to the spread of ideas in the so-called web 2.0. I have to rectify myself: they are actually talking about very similar topics, albeit with varying degrees of optimism (and realism), different empirical foundations, and approaches.

Dr. Watts, the academic, the realist, is one of the leading figures of the science of networks, a relatively new discipline that draws its theoretical frameworks from physics, mathematics, biology, sociology and other sciences. His main object of study are small-world networks, a project that spans since his time in the Department of Theoretical and Applied Mechanics at Cornell University, done in collaboration with his adviser Prof. Steve H. Strogratz. Revisiting the “Small World Experiment“, the seminal work of social psychologist Dr. Stanley Milgram which gave legs to the myth of the “Six Degrees of Separation“, Strogratz and Watts developed, with the help of modern computing muscle, a mathematical model to study the phenomenon, in which any given person can be connected to anyone in the world through a small chain of just five connections.

In his book Watts gives a very thorough explanation of the small-world phenomenon and other types of network, making a very solid case for the science of networks and its possible applications. The reading is insightful and the requirement of mathematical knowledge in order to understand it, close to none. As a man of science, Watts keeps a very critical view at the phenomenon and does not fully believe that trends can start by design: “… a series of small random events — events that would go unnoticed under normal conditions — can, at the critical point, push the system into a universally organized state, giving the appearance of having been directed there strategically.” In another passage, he maintains that “… a successful cascade [information cascade, in the language of economics] has far less to with the actual characteristics of the innovation or even the innovator, than we tend to think”, describing that a seed alone is not enough, that trees spread their seeds hoping they will land in the right place.

Gladwell is a trained science journalist and has been able to amass an interesting body of ad-hoc knowledge for his work. He’s although a bit more optimistic than Watts when it comes to the phenomenon of social contagion, or word-of-mouth epidemics. His theory is manifested in three concepts: The Law of the Few, The Stickiness Factor and The Power of Context. The first deals with “gatekeepers”, people that are able to start a social epidemic. Gladwell names them Connectors, those with very high social capital; Mavens, people with extraordinary knowledge and with a social motivation to spread it; and Salesmen, individuals with a high capacity of persuasion. The second part of theory explains how certain ideas posses a higher capacity of maintaining themselves for longer in the collective psyche, by having a higher stickiness factor. Lastly, Gladwell considers how having the proper context, or to change an existing one, is also a necessary condition to start a social epidemic.

Watts deals with a larger topic, the science of networks, but one is able to find in his work some scientific rationale to support the ideas proposed by Gladwell. Gladwell sustains a top-down, pyramid-like network, what Duncan describes in his book a “scale-free network” (Barabási and Albert, 1999), governed by a “power law”. In these networks, highly connected individuals “can have an influence that is disproportionate to their number”, ergo the Connectors, who are highly connected nodes within the network. They both explain, with varying degrees of empirical evidence and examples, that there is a moment in which ideas, trends, innovations or diseases catch on and propagate exponentially within networks, this phenomenon is called by Gladwell, the tipping point, and critical point by Watts, who says “… these changes of state are not steady and gradual, but sudden. One second is raining, the next snowing.”

The two books are by no means whatever an exhaustive explication, but they have served as a good introduction to the topic. I regret however my reading order. I started with the more scientific oriented work of Watts and moved to Gladwell’s rather business-like journalist approach to the subject. I would reverse the order if I would have to read them again.