Fields of techno-science like biotechnology develop in a network mode: disciplinary insights from different backgrounds are recombined and university-industry relations are continuously reshaped. The ongoing process of integration at the European level generates an additional network of transnational collaborations. Using the title words of scientific publications in five core journals of biotechnology, multi-variate analysis enables us to distinguish between the intellectual organization of the publications in terms of title words (variables) and the institutional structure in terms of addresses of documents (cases). The interaction among the networks in the case of biotechnology documents with European addresses is compared with the document sets with American and Japanese addresses. A complex network system of innovations is sensitive to policy interventions in ways that differ from national systems of innovation.

Cybermetric methodologies can be expected to reveal dimensions of communication other than those shown by scientometric operationalizations. In a previous study entitled â The organization of the semantic space of an author,â [1] I studied the use of words in titles of articles by Professor Tibor Braun as a scientific author. This was on the occasion of his 60th birthday. This year, on the occasion of his 70th birthday, the Internet has become available as another domain. Among other things, the Internet enables us to study the â globalizationâ of an author. Techniques and methodologies similar to the ones used in the previous (p)scientometric study will be used for the analysis of the semantic space of â Tibor Braunâ as a search term. The globalization of â Tibor Braunâ can then be visualized by using a simulation.

India's contribution to research in agriculture and related fields is assessed from an analysis of publications indexed in CAB Abstracts. CAB Abstracts indexed 51,761 papers, including about 48,300 journal articles, from more than 3,330 addresses in over 800 locations, spread over 30 states/ union territories of India, in the five years 1990-1994. CAB Abstracts has classified these papers into 22 major research areas and about 250 subfields. Plants of economic importance is the leading area of research in India, followed by Animal science. The largest number of papers published are in the three subfields, viz. Pests, pathogens and biogenic diseases of plants (8,898 papers), Plant breeding and genetics (5,675 papers) and Plant production (5,231 papers). A little over 63% of these papers were published by academic institutions. Punjab Agricultural University, Ludhiana, and the Haryana Agricultural University, Hissar, have contributed more than 2370 papers each, not including papers published from other centres of these universities. Agricultural universities have published 16,555 papers and general universities 9,933. The Indian Council of Agricultural Research has accounted for 7,856 papers. Indian researchers have used more than 1950 journals from over 65 countries. About 77% of all journal articles were published in 483 Indian journals. In no other field did Indian researchers publish such a large percent of papers in Indian journals. Unlike in physics and materials science, Indian agricultural scientists have used letters journals only infrequently. Delhi, Ludhiana, Hissar and Bangalore are the leading centres of agricultural research, while Uttar Pradesh, Maharashtra. Tamil Nadu, Haryana and Karnataka are the states accounting for the largest number of papers. This report was prepared by the M.S. Swaminathan Research Institute and was submitted to NISSAT, Department of Scientific & Industrial Research, Government of India in July 1998.

This paper analyzes the tagging patterns exhibited by users of del.icio.us, to assess how collaborative tagging supports and enhances traditional ways of classifying and indexing documents. Using frequency data and co-word analysis matrices analyzed by multi-dimensional scaling, the authors discovered that tagging practices to some extent work in ways that are continuous with conventional indexing. Small numbers of tags tend to emerge by unspoken consensus, and inconsistencies follow several predictable patterns that can easily be anticipated. However, the tags also indicated intriguing practices relating to time and task which suggest the presence of an extra dimension in classification and organization, a dimension which conventional systems are unable to facilitate.

UWO Intellectual Property Workshop, London, ON, January 20-22, 2005 / This study examined the growth pattern, authorship and publication characteristics of the professional and academic library and information science literature on the subject of copyright from 1984 to 2003 based on a subject search of the descriptor field in the Library Literature database. The literature was found to have a non-linear growth pattern which appears to be strongly affected by significant moments in copyright legislation over the 20 year period of the study. Authorship trends did not follow Lotka's law, with a significantly higher proportion of authors contributing only 1 article. The spread of authorship suggests that the most prolific authors in this area tend to be professional librarians or academics who publish extensively in the professional literature. The majority of documents in this area are journals, suggesting an emphasis on rapid dissemination of knowledge. Journal publication trends followed Bradford's law with the majority of journals contributing fewer than 1 article per year of the study.

Artificial Intelligence Lab, Department of MIS, University of Arizona / We propose a methodology to collect, quantify and visualize qualitative consumer data. We employ a Web-based Group Support System (GSS), GSw,b, to elicit free-form comments and a prototype comment analysis support system to facilitate comment classification, categorization and visualization to measure attitudes. We argue that such a methodology is needed due to the proliferation of qualitative data, the limitations of qualitative data analysis and the dearth of methods to measure attitudes contained within free-form comments. We conducted two experiments to compare our methodology with two long-established traditional methods, Likert scale evaluations and first-week box office sales records. We found that our methodology provides equivalent and superior affective and evaluative attitude information, compared to Likert scale ratings. We also found that comment analysis more accurately reflected actual first-week box office sales than did Likert scale ratings. Comment analysis with the prototype tool was seventy-five percent more efficient than manual coding. We designed the prototype to generate visualizations to make sense of multiple attitude dimensions through at-a-glance understanding and comparative presentation. The methodology we propose overcomes drawbacks often associated with qualitative data analysis and offers marketers and researchers a method to measure attitudes from free-form comments. The results indicate that qualitative data in the form of freeform comments may be quantified and visualized to provide meaningful attitude assessment. Finally, we present future research directions to enhance data collection and the comment analysis support system.

This is chapter 1 of the book (first 25 pages of a book with 392 pages). How can an economy based on something as volatile as knowledge be sustained? The urgency of improving our understanding of a knowledge-based economy provides the context and necessity of this study. In a previous study entitled A Sociological Theory of Communications: The Self-Organization of the Knowledge-based Society (2001) the author specified knowledge-based systems from a sociological perspective. In this book, he takes this theory one step further and demonstrates how the knowledge base of an economic system can be operationalized, both in terms of measurement and by providing simulation models. Loet Leydesdorff (Ph.D. Sociology, M.A. Philosophy, and M.Sc. Biochemistry) reads Science and Technology Dynamics at the Amsterdam School of Communications Research (ASCoR), University of Amsterdam. He has published extensively in science and technology studies about the Triple Helix of university-industry-government relations, scientometrics, systems theory, social network analysis, and the sociology of innovation. He received the Derek de Solla Price Award for Scientometrics and Informetrics in 2003. In 2005, he held â The City of Lausanneâ Honor Chair at the School of Economics, Université de Lausanne, Switzerland. This interdisciplinary study provides both models of the knowledge base of an economy and instruments for its measurement, as applied to the German and Dutch economies in terms of regional and sectorial differences. The simulations introduce a set of algorithms for modeling various forms of anticipation in social networks. The knowledge base of an economy can be specified as a strongly anticipatory dynamic that operates at the supra-individual level.

Connections 2006 in Syracuse, NY, May 20-21 / This study analyses the tagging patterns exhibited by users of del.icio.us and citeulike. Frequency data, coword analysis and thesaural comparisons are used to examine tagging practices and determine where they are continuous or discontinuous with traditional classification and indexing. Results show many commonalities and some intriguing differences.

Artificial Intelligence Lab, Department of MIS, University of Arizona / Recommender systems are being widely applied in many application settings to suggest products, services, and information items to potential consumers. Collaborative filtering, the most successful recommendation approach, makes recommendations based on past transactions and feedback from consumers sharing similar interests. A major problem limiting the usefulness of collaborative filtering is the sparsity problem, which refers to a situation in which transactional or feedback data is sparse and insufficient to identify similarities in consumer interests. In this article, we propose to deal with this sparsity problem by applying an associative retrieval framework and related spreading activation algorithms to explore transitive associations among consumers through their past transactions and feedback. Such transitive associations are a valuable source of information to help infer consumer interests and can be explored to deal with the sparsity problem. To evaluate the effectiveness of our approach, we have conducted an experimental study using a data set from an online bookstore. We experimented with three spreading activation algorithms including a constrained Leaky Capacitor algorithm, a branch-and-bound serial symbolic search algorithm, and a Hopfield net parallel relaxation search algorithm. These algorithms were compared with several collaborative filtering approaches that do not consider the transitive associations: a simple graph search approach, two variations of the user-based approach, and an item-based approach. Our experimental results indicate that spreading activation-based approaches significantly outperformed the other collaborative filtering methods as measured by recommendation precision, recall, the F-measure, and the rank score.We also observed the over-activation effect of the spreading activation approach, that is, incorporating transitive associations with past transactional data that is not sparse may “dilute” the data used to infer user preferences and lead to degradation in recommendation performance.

Bibliometric measures for evaluating research units in the book-oriented humanities and social sciences are underdeveloped relative to those available for journal-oriented science and technology. We therefore present a new measure designed for book-oriented fields: the â libcitation count.â This is a count of the libraries holding a given book, as reported in a national or international union catalog. As librarians decide what to acquire for the audiences they serve, they jointly constitute an instrument for gauging the cultural impact of books. Their decisions are informed by knowledge not only of audiences but also of the book world, e.g., the reputations of authors and the prestige of publishers. From libcitation counts, measures can be derived for comparing research units. Here, we imagine a matchup between the departments of history, philosophy, and political science at the University of New South Wales and the University of Sydney in Australia. We chose the 12 books from each department that had thehighest libcitation counts in the Libraries Australia union catalog during 2000â 2006. We present each bookâ s raw libcitation count, its rank within its LC class, and its LC-class normalized libcitation score. The latter is patterned on the item-oriented field normalized citation score used in evaluative bibliometrics. Summary statistics based on these measures allow the departments to be compared for cultural impact. Our work has implications for programs such as Excellence in Research for Australia and the Research Assessment Exercise in the United Kingdom. It also has implications for data mining in OCLCâ s WorldCat.