By the way, I found this on Daniella Thompson’s on Brazil blog.

Of course this shows only the nice sides of those times. But if one just look at the state, or the lack of State, that Rio is today…

Via: Rio em Disco

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.

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.

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.

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.

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?

“If you have an apple and I have an apple and we exchange these apples then you and I will still each have one apple. But if you have an idea and I have an idea and we exchange these ideas, then each of us will have two ideas.”

It verbalizes very simply — of course, and poetically — the whole issue about copyright vs. read-and-write culture, collaborative knowledge and the democratization of the means of intellectual production. I found this upon reading a text from Sérgio Amadeu, one of the champions of the free-software movement in Brazil. It’s a fierce defense of the values of cultural diversity through digital diversity. The text is here. (only in Brazilian Portuguese)

General data for both searches (blog and news)

Chart 1: entries per day (with all key words combined)

Chart 2: entries per day of the week (all keywords combined)

Blog search

Chart 3: entries per day (broken down by subscription)

Chart 4: ratio between unique and repeated entries

Chart 5: preselections and bookmarks per day, next to unique and total entries

News search

Chart 6: entries per day (broken down by subscription)

Chart 7: ratio between unique and repeated entries

Chart 8: preselections and bookmarks per day, next to unique and total entries

Some obvious things first

Observing charts 3 and 6, where the number of new feeds per day are broken down into the specific searches, say, “dissemination knowledge culture web 2.0″ and “culture 2.0″, we can notice that the less keywords used, at least in this very specific scenario, the higher the number of results achieved. This should not by any means come as a surprise, as it is also with their results: less keywords yield more general results.

Gruhl et al. [1] have found in a study about information diffusion of information through the blogosphere, in which they analyzed a set of 401.021 postings, with an average of 2k-10k posts per day, among 11,804 RSS feeds, that weekends are low in intensity while midweek peak. As my humble observation shows, this is also the case here.

Number of unique entries

When comparing charts 4 and 7, one can clearly notice that the blog search turn up a much higher ratio of unique entries: 81.5 % of the blog search feeds where unique, whereas only about half of the news feeds (56.85%) where not repeated. I assume that this has to do with how many blogs there are in the blogosphere, compared to the rather limited universe of news providers searched by Google. What I also realized during the collection phase, is that many news feeds tend to be repeated during 1-2 cycle, therefore showing up in the next day of collection. Naturally, the set of keywords, which is progressively reduced in complexity but still with some of the same words, the results showed within the more complex ones (with more words) are likely to be shown also on those of lower complexity (with less words).

Preselections and bookmarks

Charts 5 and 8 show the number of preselections and bookmarks for both the blog and news searches. Here is clear that the blogosphere is a much more fertile ground when it comes to results. Of all unique entries, 18.16 % of the blog feeds were preselected for further reading (adding star in Google Reader), while only 9.04 % of the news feeds have resulted in preselections. In relation to the total amout of entries (unique and non-unique), this difference becomes even more blatant: 14.80% of all blog search feeds became preselections, and as opposed to a third of that (5.14%) in the news search.

Bookmarks stretch the difference even further. In the blog search the number of bookmarked entries is of 6.69 % of all unique entries and 5.45 % of all entries. This figures are 2.11% and 1.20% for the news search respectively. That means that the blog searcher returns nearly 3 times more of bookmarks than the news search, and almost 5 times as much when all the entries are taken into consideration.

[1] D. Gruhl, R. V. Guha, D. Liben-Nowell, and A. Tomkins. Information di®usion through blogspace.
In WWW, pages 491{501, 2004.

Via: Jerz’s Literacy Weblog