Search (85 results, page 1 of 5)

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Abstract

This article considers the relationships among meaning generation, selection, and the dynamics of discourse from a variety of perspectives ranging from information theory and biology to sociology. Following Husserl's idea of a horizon of meanings in intersubjective communication, we propose a way in which, using Shannon's equations, the generation and selection of meanings from a horizon of possibilities can be considered probabilistically. The information-theoretical dynamics we articulate considers a process of meaning generation within cultural evolution: information is imbued with meaning, and through this process, the number of options for the selection of meaning in discourse proliferates. The redundancy of possible meanings contributes to a codification of expectations within the discourse. Unlike hardwired DNA, the codes of nonbiological systems can coevolve with the variations. Spanning horizons of meaning, the codes structure the communications as selection environments that shape discourses. Discursive knowledge can be considered as meta-coded communication that enables us to translate among differently coded communications. The dynamics of discursive knowledge production can thus infuse the historical dynamics with a cultural evolution by adding options, that is, by increasing redundancy. A calculus of redundancy is presented as an indicator whereby these dynamics of discourse and meaning may be explored empirically.

Date

29. 9.2018 11:22:09

Source

Journal of the Association for Information Science and Technology. 69(2018) no.10, S.1181-1192

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Abstract

We present a novel approach to visually locate bodies of research within the sciences, both at each moment of time and dynamically. This article describes how this approach fits with other efforts to locally and globally map scientific outputs. We then show how these science overlay maps help benchmarking, explore collaborations, and track temporal changes, using examples of universities, corporations, funding agencies, and research topics. We address their conditions of application and discuss advantages, downsides, and limitations. Overlay maps especially help investigate the increasing number of scientific developments and organizations that do not fit within traditional disciplinary categories. We make these tools available online to enable researchers to explore the ongoing sociocognitive transformations of science and technology systems.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.9, S.1871-1887

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Abstract

The study of interhuman communication requires a more complex framework than Claude E. Shannon's (1948) mathematical theory of communication because "information" is defined in the latter case as meaningless uncertainty. Assuming that meaning cannot be communicated, we extend Shannon's theory by defining mutual redundancy as a positional counterpart of the relational communication of information. Mutual redundancy indicates the surplus of meanings that can be provided to the exchanges in reflexive communications. The information is redundant because it is based on "pure sets" (i.e., without subtraction of mutual information in the overlaps). We show that in the three-dimensional case (e.g., of a triple helix of university-industry-government relations), mutual redundancy is equal to mutual information (Rxyz = Txyz); but when the dimensionality is even, the sign is different. We generalize to the measurement in N dimensions and proceed to the interpretation. Using Niklas Luhmann's (1984-1995) social systems theory and/or Anthony Giddens's (1979, 1984) structuration theory, mutual redundancy can be provided with an interpretation in the sociological case: Different meaning-processing structures code and decode with other algorithms. A surplus of ("absent") options can then be generated that add to the redundancy. Luhmann's "functional (sub)systems" of expectations or Giddens's "rule-resource sets" are positioned mutually, but coupled operationally in events or "instantiated" in actions. Shannon-type information is generated by the mediation, but the "structures" are (re-)positioned toward one another as sets of (potentially counterfactual) expectations. The structural differences among the coding and decoding algorithms provide a source of additional options in reflexive and anticipatory communications.

Date

29. 1.2014 16:44:54

Source

Journal of the Association for Information Science and Technology. 65(2014) no.2, S.386-399

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Abstract

The communication of meaning as distinct from (Shannon-type) information is central to Luhmann's social systems theory and Giddens' structuration theory of action. These theories share an emphasis on reflexivity, but focus on meaning along a divide between interhuman communication and intentful action as two different systems of reference. Recombining these two theories into a theory about the structuration of expectations, interactions, organization, and self-organization of intentional communications can be simulated based on algorithms from the computation of anticipatory systems. The self-organizing and organizing layers remain rooted in the double contingency of the human encounter, which provides the variation. Organization and self-organization of communication are reflexive upon and therefore reconstructive of each other. Using mutual information in three dimensions, the imprint of meaning processing in the modeling system on the historical organization of uncertainty in the modeled system can be measured. This is shown empirically in the case of intellectual organization as "structurating" structure in the textual domain of scientific articles.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.10, S.2138-2150

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Abstract

Normalization of citation scores using reference sets based on Web of Science subject categories (WCs) has become an established ("best") practice in evaluative bibliometrics. For example, the Times Higher Education World University Rankings are, among other things, based on this operationalization. However, WCs were developed decades ago for the purpose of information retrieval and evolved incrementally with the database; the classification is machine-based and partially manually corrected. Using the WC "information science & library science" and the WCs attributed to journals in the field of "science and technology studies," we show that WCs do not provide sufficient analytical clarity to carry bibliometric normalization in evaluation practices because of "indexer effects." Can the compliance with "best practices" be replaced with an ambition to develop "best possible practices"? New research questions can then be envisaged.

Aid

Web of Science

Source

Journal of the Association for Information Science and Technology. 67(2016) no.3, S.707-714

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Abstract

The relationship between the "knowledge base" and the "globalization" of communication systems is discussed from the perspective of communication theory. I argue that inter-human communication takes place at two levels. At the first level information is exchanged and provided with meaning and at the second level meaning can reflexively be communicated. Human language can be considered as the evolutionary achievement which enables us to use these two channels of communication simultaneously. Providing meaning with hindsight is a recursive operation: a meaning that makes a difference can be considered as knowledge. If the production of knowledge is socially organized, the perspective of hindsight can further be codified. This adds globalization to the historically stabilized patterns of communications. Globalization can be expected to transform the communications in an evolutionary mode. However, the self-organization of a knowledge-based society remains an expectation with the status of a hypothesis.

Date

22. 5.2003 19:48:04

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Abstract

This paper explores the ISI Journal Citation Reports (JCR) bibliographic and subject structures through Library of Congress (LC) and American research libraries cataloging and classification methodology. The 2006 Science Citation Index JCR Behavioral Sciences subject category journals are used as an example. From the library perspective, the main fault of the JCR bibliographic structure is that the JCR mistakenly identifies journal title segments as journal bibliographic entities, seriously affecting journal rankings by total cites and the impact factor. In respect to JCR subject structure, the title segment, which constitutes the JCR bibliographic basis, is posited as the best bibliographic entity for the citation measurement of journal subject relationships. Through factor analysis and other methods, the JCR subject categorization of journals is tested against their LC subject headings and classification. The finding is that JCR and library journal subject analyses corroborate, clarify, and correct each other.

Source

Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1097-1117

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Abstract

Citation analysis of documents retrieved from the Medline database (at the Web of Knowledge) has been possible only on a case-by-case basis. A technique is presented here for citation analysis in batch mode using both Medical Subject Headings (MeSH) at the Web of Knowledge and the Science Citation Index at the Web of Science (WoS). This freeware routine is applied to the case of "Brugada Syndrome," a specific disease and field of research (since 1992). The journals containing these publications, for example, are attributed to WoS categories other than "cardiac and cardiovascular systems", perhaps because of the possibility of genetic testing for this syndrome in the clinic. With this routine, all the instruments available for citation analysis can now be used on the basis of MeSH terms. Other options for crossing between Medline, WoS, and Scopus are also reviewed.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1076-1080

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Abstract

In bibliometrics, the association of "impact" with central-tendency statistics is mistaken. Impacts add up, and citation curves therefore should be integrated instead of averaged. For example, the journals MIS Quarterly and Journal of the American Society for Information Science and Technology differ by a factor of 2 in terms of their respective impact factors (IF), but the journal with the lower IF has the higher impact. Using percentile ranks (e.g., top-1%, top-10%, etc.), an Integrated Impact Indicator (I3) can be based on integration of the citation curves, but after normalization of the citation curves to the same scale. The results across document sets can be compared as percentages of the total impact of a reference set. Total number of citations, however, should not be used instead because the shape of the citation curves is then not appreciated. I3 can be applied to any document set and any citation window. The results of the integration (summation) are fully decomposable in terms of journals or institutional units such as nations, universities, and so on because percentile ranks are determined at the paper level. In this study, we first compare I3 with IFs for the journals in two Institute for Scientific Information subject categories ("Information Science & Library Science" and "Multidisciplinary Sciences"). The library and information science set is additionally decomposed in terms of nations. Policy implications of this possible paradigm shift in citation impact analysis are specified.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.11, S.2133-2146

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Abstract

As a follow-up to the highly cited authors list published by Thomson Reuters in June 2014, we analyzed the top 1% most frequently cited papers published between 2002 and 2012 included in the Web of Science (WoS) subject category "Information Science & Library Science." In all, 798 authors contributed to 305 top 1% publications; these authors were employed at 275 institutions. The authors at Harvard University contributed the largest number of papers, when the addresses are whole-number counted. However, Leiden University leads the ranking if fractional counting is used. Twenty-three of the 798 authors were also listed as most highly cited authors by Thomson Reuters in June 2014 (http://highlycited.com/). Twelve of these 23 authors were involved in publishing 4 or more of the 305 papers under study. Analysis of coauthorship relations among the 798 highly cited scientists shows that coauthorships are based on common interests in a specific topic. Three topics were important between 2002 and 2012: (a) collection and exploitation of information in clinical practices; (b) use of the Internet in public communication and commerce; and (c) scientometrics.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3095-3100

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Abstract

Using data from the Web of Science (WoS), we analyze the mutual information among university, industry, and government addresses (U-I-G) at the country level for a number of countries. The dynamic evolution of the Triple Helix can thus be compared among developed and developing nations in terms of cross-sectional coauthorship relations. The results show that the Triple Helix interactions among the three subsystems U-I-G become less intensive over time, but unequally for different countries. We suggest that globalization erodes local Triple Helix relations and thus can be expected to have increased differentiation in national systems since the mid-1990s. This effect of globalization is more pronounced in developed countries than in developing ones. In the dynamic analysis, we focus on a more detailed comparison between China and the United States. Specifically, the Chinese Academy of the (Social) Sciences is changing increasingly from a public research institute to an academic one, and this has a measurable effect on China's position in the globalization.

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2317-2325

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Abstract

As a complement to Nelson and Winter's (1977) article titled "In Search of a Useful Theory of Innovation," a sociological perspective on innovation networks can be elaborated using Luhmann's social systems theory, on the one hand, and Latour's "sociology of translations," on the other. Because of a common focus on communication, these perspectives can be combined as a set of methodologies. Latour's sociology of translations specifies a mechanism for generating variation in relations ("associations"), whereas Luhmann's systems perspective enables the specification of (functionally different) selection environments such as markets, professional organizations, and political control. Selection environments can be considered as mechanisms of social coordination that can self-organize-beyond the control of human agency-into regimes in terms of interacting codes of communication. Unlike relatively globalized regimes, technological trajectories are organized locally in "landscapes." A resulting "duality of structure" (Giddens, 1979) between the historical organization of trajectories and evolutionary self-organization at the regime level can be expected to drive innovation cycles. Reflexive translations add a third layer of perspectives to (a) the relational analysis of observable links that shape trajectories and (b) the positional analysis of networks in terms of latent dimensions. These three operations can be studied in a single framework, but using different methodologies. Latour's first-order associations can then be analytically distinguished from second-order translations in terms of requiring other communicative competencies. The resulting operations remain infrareflexively nested, and can therefore be used for innovative reconstructions of previously constructed boundaries.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2359-2374

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Abstract

We measure synergy for the Russian national, provincial, and regional innovation systems as reduction of uncertainty using mutual information among the 3 distributions of firm sizes, technological knowledge bases of firms, and geographical locations. Half a million units of data at firm level in 2011 were obtained from the OrbisT database of Bureau Van Dijk. The firm level data were aggregated at the levels of 8 Federal Districts, the regional level of 83 Federal Subjects, and the single level of the Russian Federation. Not surprisingly, the knowledge base of the economy is concentrated in the Moscow region (22.8%) and Saint Petersburg (4.0%). Except in Moscow itself, high-tech manufacturing does not add synergy to any other unit at any of the various levels of geographical granularity; instead it disturbs regional coordination. Knowledge-intensive services (KIS; including laboratories) contribute to the synergy in all Federal Districts (except the North-Caucasian Federal District), but only in 30 of the 83 Federal Subjects. The synergy in KIS is concentrated in centers of administration. The knowledge-intensive services (which are often state affiliated) provide backbone to an emerging knowledge-based economy at the level of Federal Districts, but the economy is otherwise not knowledge based (except for the Moscow region).

Source

Journal of the Association for Information Science and Technology. 66(2015) no.6, S.1229-1238

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Abstract

Using information theory, we measure innovation systemness as synergy among size-classes, ZIP Codes, and technological classes (NACE-codes) for 8.5 million American companies. The synergy at the national level is decomposed at the level of states, Core-Based Statistical Areas (CBSA), and Combined Statistical Areas (CSA). We zoom in to the state of California and in more detail to Silicon Valley. Our results do not support the assumption of a national system of innovations in the U.S.A. Innovation systems appear to operate at the level of the states; the CBSA are too small, so that systemness spills across their borders. Decomposition of the sample in terms of high-tech manufacturing (HTM), medium-high-tech manufacturing (MHTM), knowledge-intensive services (KIS), and high-tech services (HTKIS) does not change this pattern, but refines it. The East Coast-New Jersey, Boston, and New York-and California are the major players, with Texas a third one in the case of HTKIS. Chicago and industrial centers in the Midwest also contribute synergy. Within California, Los Angeles contributes synergy in the sectors of manufacturing, the San Francisco area in KIS. KIS in Silicon Valley and the Bay Area-a CSA composed of seven CBSA-spill over to other regions and even globally.

Source

Journal of the Association for Information Science and Technology. 70(2019) no.10, S.1108-1123

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Abstract

We argue that the communication structures in the Chinese social sciences have not yet been sufficiently reformed. Citation patterns among Chinese domestic journals in three subject areas - political science and Marxism, library and information science, and economics - are compared with their counterparts internationally. Like their colleagues in the natural and life sciences, Chinese scholars in the social sciences provide fewer references to journal publications than their international counterparts; like their international colleagues, social scientists provide fewer references than natural sciences. The resulting citation networks, therefore, are sparse. Nevertheless, the citation structures clearly suggest that the Chinese social sciences are far less specialized in terms of disciplinary delineations than their international counterparts. Marxism studies are more established than political science in China. In terms of the impact of the Chinese political system on academic fields, disciplines closely related to the political system are less specialized than those weakly related. In the discussion section, we explore reasons that may cause the current stagnation and provide policy recommendations.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.7, S.1360-1376

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Abstract

Co-occurrence matrices, such as cocitation, coword, and colink matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of these data. The underlying problem, in our opinion, involved understanding the nature of various types of matrices. This article discusses the difference between a symmetrical cocitation matrix and an asymmetrical citation matrix as well as the appropriate statistical techniques that can be applied to each of these matrices, respectively. Similarity measures (such as the Pearson correlation coefficient or the cosine) should not be applied to the symmetrical cocitation matrix but can be applied to the asymmetrical citation matrix to derive the proximity matrix. The argument is illustrated with examples. The study then extends the application of co-occurrence matrices to the Web environment, in which the nature of the available data and thus data collection methods are different from those of traditional databases such as the Science Citation Index. A set of data collected with the Google Scholar search engine is analyzed by using both the traditional methods of multivariate analysis and the new visualization software Pajek, which is based on social network analysis and graph theory.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.12, S.1616-1628

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Abstract

"Citation classics" are not only highly cited, but also cited during several decades. We explore whether the peaks in the spectrograms generated by Reference Publication Years Spectroscopy (RPYS) indicate such long-term impact by comparing across RPYS for subsequent time intervals. Multi-RPYS enables us to distinguish between short-term citation peaks at the research front that decay within 10 years versus historically constitutive (long-term) citations that function as concept symbols. Using these constitutive citations, one is able to cluster document sets (e.g., journals) in terms of intellectually shared histories. We test this premise by clustering 40 journals in the Web of Science Category of Information and Library Science using multi-RPYS. It follows that RPYS can not only be used for retrieving roots of sets under study (cited), but also for algorithmic historiography of the citing sets. Significant references are historically rooted symbols among other citations that function as currency.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1224-1233

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Abstract

Based on the complete set of firm data for Sweden (N = 1,187,421; November 2011), we analyze the mutual information among the geographical, technological, and organizational distributions in terms of synergies at regional and national levels. Using this measure, the interaction among three dimensions can become negative and thus indicate a net export of uncertainty by a system or, in other words, synergy in how knowledge functions are distributed over the carriers. Aggregation at the regional level (NUTS3) of the data organized at the municipal level (NUTS5) shows that 48.5% of the regional synergy is provided by the 3 metropolitan regions of Stockholm, Gothenburg, and Malmö/Lund. Sweden can be considered a centralized and hierarchically organized system. Our results accord with other statistics, but this triple helix indicator measures synergy more specifically and quantitatively. The analysis also provides us with validation for using this measure in previous studies of more regionalized systems of innovation (such as Hungary and Norway).

Source

Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1890-1902

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Abstract

The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics-Why should one use the mean and not the median?-and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.

Date

22. 1.2011 12:51:07

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.217-229

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Abstract

Aggregated journal-journal citations can be used for mapping the intellectual organization of the sciences in terms of specialties because the latter can be considered as interreading communities. Can the journal-journal citations also be used as early indicators of change by comparing the files for two subsequent years? Probabilistic entropy measures enable us to analyze changes in large datasets at different levels of aggregation and in considerable detail. Compares Journal Citation Reports of the Social Science Citation Index for 1999 with similar data for 1998 and analyzes the differences using these measures. Compares the various indicators with similar developments in the Science Citation Index. Specialty formation seems a more important mechanism in the development of the social sciences than in the natural and life sciences, but the developments in the social sciences are volatile. The use of aggregate statistics based on the Science Citation Index is ill-advised in the case of the social sciences because of structural differences in the underlying dynamics.

Date

6.11.2005 19:02:22