Over the last month or so, a number of incidents have occurred that cause me to reflect on social capital and “Web 2.0”. I was surprised looking back on the BLOG that I had not addressed this issue directly in any of the posts. The need to address this topic began with an oversight board for the school. Last year, they advised the Dean that we should be doing more on social networking and Web 2.0. When I heard that was going to become a priority, I was a little perturbed. As far as I was concerned, we (and particularly I) had been working in this area for almost a decade. The fact that the board was not apprised of this work bothered me. At first, I blamed the Dean for not being aware of the work. In the last analysis, I blame myself for not talking more about it. This year, I made a presentation to the board in which I reviewed some of our work. I was pleased to hear that they were favorably impressed with our attention to the matter.
A part of the presentation had to do with work on collaborative authoring funded by NIST in the late nineties and doctoral dissertations that resulted from that work. We built a system that was designed to speed international standards development. In many ways we succeeded, but like so many other basic initiatives of that period, our work was swamped by the tsunami known as the World Wide Web. Two of the dissertations that came out of that work included Bordin Sapsomboon’s “Shared Defect Detection : The Effects of Annotations in Asynchronous Software Inspection” and Vichita Vathanophas’s “The Use Of Peripheral Social Awareness Tools In Collaborative Systems.” Both dissertations were published in 2000. Bordin’s was very traditional and demonstrated that defect detection could be improved using social software inspection. Vichita’s was more radical. She used the extensive logs maintained by the system to provide an indication of how people felt about the project they were working on and how willing they would be to contribute. For many, her dissertation smacked of big brother. I believe that what she was doing in the late nineties was no different than what is happing today. It was simply that the data collection and use was more explicit. Both of these dissertations demonstrated well controlled studies of the impact of social networking systems.
Shortly after I made the presentation to the Board, I was asked to speak to various groups of students about the topic. In that process, I began to use the terms aggregate annotations and social capital as an important concepts behind social networking and social tagging systems. I have addressed the issue of aggregate annotations in another post on this blog. (See my Seminar on Annotation Aggregation for more information.) Someone asked me about the term “social capital” and I did a web search so as to give them a reference. I was surprised to find one of my website pages on the first page of the search results! I found it referred to a doctoral seminar I gave in January of 1997. The seminar was inspired by a talk Robert Putnam had given at the first annual conference on leveraging cyberspace in October of 1996, which was co-sponsored by XEROX PARC and NIST. I had been invited to talk about Multi-level Navigation of Document Spaces. At this inaugural, and final, conference I was mesmerized by Robert Putnam, Marc Weiser, John Seeley Brown, and Paul Saffo. Truth be told, I thought every presenter at that intimate conference was spectacular. (See http://nvl.nist.gov/pub/nistpubs/jres/102/3/j23mol.pdf.) Returning from the conference, with Robert Putnam’s research and challenge clear in my mind, I wrote up the charge for the doctoral seminar. It began with the following:
This seminar explores two questions. The first question is "what is social capital?" Assuming we can come to a consensus answer to this question along the lines that have already been suggested by Putnam and others, the second and more interesting question to be addressed in this seminar is "how might systems be designed to prevent the erosion of, or encourage the development of, social capital?" (see my Seminar on Social Capital.)Would that I had followed up intelligently on my own hunch, I might not be writing about this, but sitting on top of linked-in or one of the other social networking sites!
Fast forwarding to today, we might ask a similar questions. “What is Web 2.0 and where are we going?” Personally, given all the confusion about Web2.0, Web3.0 and all of the technologies and applications, my personal preference is to ask what the Next Generation Web (NGW) might look like. In June of 2008, Cormode and Krishnamurthy of ATT Labs published a wonderful article on the evolution of the Web. In my opinion it is the single most intelligent article on the topic. (See Graham Cormode and Balachander Krishnamurthy, Key differences between Web 1.0 and Web 2.0. First Monday, Volume 13 Number 6 - 2 June 2008.) The article is worth reading in its entirety several times. For purposes of this discussion, I combine several of their elegant observations as follows:
Moving forward, how do we understand what is going on and more importantly predict where we might productively move? It may be that the call for Web Science by Tim Berners-Lee and others is the answer. Being somewhat more of a traditionalist, I like the arguments put forward by Ed Chi of PARC. (See Ed H. Chi,The Social Web: Research and Opportunities, IEEE Computer, Volume 41 Number 9,September 2008, pp88-91) Chi begins with a suggestion that the social web currently consists of three kinds of activities – information foraging, sharing and tagging, and collaborative creation. It makes sense to me to think about research aimed at “developing new theories and algorithms to model, mine, and understand socially constructed knowledge structures and social information networks.” This may indeed be exactly the same goal as others would set for “Web Science.” For me, the name of the discipline is not as important as the research questions. We have enough flexibility within our current disciplines to reach out collaboratively to address the basic questions. What is most important is that we forge intelligent questions based on a grounded conceptual framework.
Two final notes. I need to write a post for this blog on Knowledge Management and Collective Intelligence. Over the years, I have talked with disdain about these topics. Over the last couple years, I have changed my position. It is becoming clear to me that there are occasions when it is important to make tacit knowledge explicit. Indeed, this has become for me the mantra of knowledge management. The example that I use most frequently relates to the vast store of knowledge that existed in the brains of nuclear engineers who worked for Westinghouse. With the resurgence of interest in nuclear power, it has become apparent to some that the vast store of knowledge that existed in the heads of those engineers has diminished as they have retired and passed away. If some kind of social system to capture this information had been in place at Westinghouse over that last 50 years, it might be possible today to go back and harvest the nuggets of knowledge and resurrect a nuclear program at Westinghouse more easily than will now be possible. IBM and others have recognized this and begun to develop aggressive program that may serve to allow for better knowledge management.
Regarding collective intelligence, I have had a similar epiphany. It is based mainly on the work of one of my recent PhD students, Worasit Choochaiwattana, who developed a retrieval system based on the social bookmarking site delicious. The research was able to show that resources retrieved through his system were rated as slightly better than those retrieved by Google. The key here is that the set of resources used in his system was much smaller than the set used in Google – by three orders of magnitude. The implication of this finding for the size of the server farm needed as the base for the search engine is staggering. What makes this possible? There are two things. First and foremost are the rather brilliant algorithms Worasit developed. Second, and equally significant, along a very different dimension, is the filtering of the resources on which the search was conducted. As anyone who has searched recently understands, the number of “noise” resources that are returned as highly ranked is on the increase. Personally, I find little comfort in the fact that many other people have encountered the same problems I encounter. It used to be when I searched, I found people who were answering the question. Today, I find many people who are asking the same question. As it ends up, people don’t bookmark question pages much. They tend to bookmark pages with answers. It is this collective intelligence of bookmarking that delicious harvests. You may suggest that this is more common sense than intelligence, and I won’t argue. At the same time, I am coming to believe that we will find important ways to make use of this phenomenon, whatever we choose to call it. Personally, I am not opposed to calling it collective intelligence.
In conclusion, there are rich histories of the study of important concepts such as social capital which might inform our invention of a second generation of the web. It is important to rise above the rapid evolution of the web and the technologies employed and ask simple fundamental questions about what is going on. One of the most central of these concepts is that of social capital. Others include collective intelligence and annotation aggregation. At heart, the next generation web is about people as first class entities!