No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Conceptualization of science using collaboration and competences
Abstract
Purpose
The purpose of this paper is to propose an approach for conceptualizing science based on collaboration and competences of researchers.
Design/methodology/approach
The research is conducted by exploratory analysis of collaboration and competences using case studies from humanistic, engineering, natural sciences and a general topic.
Findings
The findings show that by applying the proposed approach on bibliographic data that readily exist for many national sciences as well as for international scientific communities, one can obtain useful new insights into the research. The approach is demonstrated with the following exploratory findings: identification of important connections and individual researchers that connect the community of anthropologists; collaboration of technical scientists in the community of anthropologists caused by an interdisciplinary research project; connectivity, interdisciplinary and structure of artificial intelligence, nanotechnology and a community based on a general topic; and identifying research interest shift described with concretization and topic-shift.
Practical implications
As demonstrated with the practical implementation ( http://scienceatlas.ijs.si/ ), users can obtain information of the most relevant competences of a researcher and his most important collaborators. It is possible to obtaining researchers, community structure and competences of an arbitrary research topic.
Social implications
The map for collaboration and competences of a complete science can be a crucial tool for policy-making. Social scientists can use the results of the proposed approach to better understand and direct the development of science.
Originality/value
Originality and value of the paper is in combining text (competences) and network (research collaboration and co-authoring) approaches for exploring science. Additional values give the results of analysis that demonstrate the approach.
... Hu and Zhang (2017) combining various informational methods (co-occurrence, descriptive statistics, and topological network maps) to reveal the structure and pattern of collaboration. Collaboration graph and competence map is proposed as an approach for conceptualizing science (Karlovcec et al., 2016). The crosslagged panel model is used to analyze the relationship between research productivity, collaboration, and determination (Abramo, D'Angelo and Murgia, 2017). ...
... The results of the analysis used publications from five research universities in Malaysia indexed by Scopus totaling 22,244 articles published between 2008 and October 2011. Table 6 The growth of interurban collaborations between 2000 and 2007 Table 7 Disciplines with extensive international collaboration Research conducted in Slovenia (Karlovcec et al., 2016) in the topic of conceptualize of science based on collaboration and competence. The study was analyse publications from researchers concerning: topics, nodes, links to community, cluster and interdisciplinary communities, and research interests. ...
Purpose – The purpose of this study is to propose a new method for revealing the collaboration frequencies among the author’s name and the author’s affiliation through various analysis and visualization methods.
Design/methodology/approach – This study takes metadata of the author’s name, author’s affiliate, and keyword from National Scientific Repository (RIN). Each article will be extracted accord to the entity, the author’s name is separated into first author, second author, third author, etc. The affiliation is also separated according to the author’s affiliation using machine learning algorithms.
Findings – The implementation of the collaboration matrix form of visualization can be used effectively in looking at the number of collaborative frequencies of scientific works among author’s names and author’s affiliations. Presentations and calculations of keywords that often appear in each scientific paper resulting from collaboration between name pairs can be used to identify the contents of the study of scientific articles as a whole, see the topics discussed and find out the trends and interests of research.
Originality/value – This study applied collaboration matrix using cooccurrence and combinatoric methods. The result of the analysis is the number of collaboration among the authors and the highest number of collaborations will be placed on the top rank.
Keywords: Co-occurrence, Combinatoric system, Collaboration matrix, Co-author network, Co-author pattern, Scientometrics
... Research on CRIS has made significant contributions to strengthen such systems and to ensure their interoperability. Contributions have been made regarding (a) processes that had allowed institutions to increase and enhance their publication count compared to previous years, when their collections were handled with a production virtually invisible to the community of specialists [14], [15]; (b) modeling, with the introduction of new publication models [16], including open access with the help of CRIS, which made it possible to establish links between individual researchers, their publications and the funding obtained; (c) development of frameworks [17] for the management of information associated with research, with a proposal to use the rapid application development method to design reusable modules and integrate frameworks to ensure the security and integration of the data [18]; (d) mapping and classifications, with proposals made for the conceptualization of science based on collaboration and mapping of the researchers' competencies [19], this type of information has been obtained from the SICRIS (Slovenian Current Research Information System), Slovenia's database of national research projects; (e) methods and tools, such as the evaluation of an exploratory project on new techniques for the development of collections at the University of Manchester Library [20], using innovative methods to ensure the construction of collections for the future and to promote automation, proposing a prospective method: to use its CRIS for the development of its collections. Also, the use of Symplectic Elements© has also been reported as a tool to more efficiently measure the impact of their research. ...
... From the studies analyzed, Table VII and Figure 6 show that the most frequent type of contribution was Process, with 36%, followed by Model with 27%, Framework, and Classification with 12% each, Mapping with 6%, and finally Method and Tool with 3%, respectively. This type of contributions coincides with the reported studies in the literature, of note being: Process [14], [15]; Model [16]; Framework [18]; Classification and Mapping [19], and Method and Tool [20]. One of the most representative articles on mapping in relation to the Process contribution states that a cluster analysis process was carried out on the bibliographic data of Slovenian researchers and the disciplines to which they belong, using their country's SICRIS, and from there it discussed the understanding of the structure of collaboration and cooperation in sciences and the research and development policies [15]. ...
Research management in relation to Research and Development (R & D) has found a comprehensive and powerful tool in the Current Research Information System (CRIS). Publications on the subject are still emerging, so knowing what research has been done and its contributions presents an opportunity to build theoretical and reference frameworks, and to identify gaps and potential opportunities for future developments in information technology. Various articles covering these systems were analyzed with the objective of identifying the research areas, countries and institutions in which they were published, as well as their research approaches, contributions and topics covered. A systematic mapping of literature was carried out, which included 33 articles published on Web of Science (WoS) and Scopus, from 2007 to 2017. To ensure valid results, the evaluation guide for researchers was used during for the design and review phases of the systematic mapping studies, as well as the corresponding evaluation rubric; in addition, a strategy to define direct decision rules on how to classify an article based on the results of evaluations of multiple researchers was adopted. The findings show that the main research areas are Information Science & Library Science and Computer Science; the largest concentration of publications is found in Europe; research focuses on Evaluation Research; contributions are oriented to create processes and models, and to describe the applications and uses of CRIS. It is concluded that there are areas of opportunity for the development of research in this area, such as the expansion of the research areas in which it is used, the possibilities of collaboration, sharing and exchange at a global level, and the coverage towards integration issues with open access.
... integrating data about 35272 researchers, 5716 projects, 82905 publications and 17190 video lectures. This too allows visualizing collaboration and competences of the researchers [9]. The evolving network ScienceAtlas of the collaborations in scientific works by Slovenian researchers, evolving over a 9-year period with 3-year leaps. ...
Networks are important representations in computer science to communicate structural aspects of a given system of interacting components. The evolution of a network has several topological properties that can provide us information on the network itself. In this paper, we present a methodology to compare the the topological characteristics of the evolution of a network, encoded into a (persistence) diagram that tracks the lifetimes of those features. This will enable us to classify the evolution of networks based on the distance between the diagrams that represent such network evolution. In that, we also consider complex vectors that bring a complementary perspective to the distance-based classification that is closer to the computational methods, aims to enhance the computational efficiency of those comparisons, and that is by itself a source of open research questions.
... В связи с этим возникает вопрос об уровнях и программах подготовки в вузах. Бакалавры и магистры библиотечных специальностей априори являются носителями этих компетенций, и можно смело утверждать, что будущие работодатели этих выпускников заинтересованы в их наличии [5,6]. ...
The author examines the role of libraries in science support. He conceptualizes multicompetence of library undergraduate students in science information acquisition and processing; specifies librarians’ professional role within modern science information infrastructure; and compares the competences required under the Federal Standards of Higher Professional Education (FGOS VPO) to those needed for efficient science support. The author concludes that future librarians have to get specific knowledge and skills at universities so they could be successful in the labor market. It is emphasized that the existing government standards of higher professional education specify only frame requirements to graduates’ competences.
The article deals with some processes generating increases of research collaboration one of the most characteristic tendencies of modern science. The major empirical focus is the increasing tendency of co-authorship in sociology in Slovenia. Bibliometric analyses, based on two joint national research information systems (SICRIS and COBISS), shows the amount of co-authored publications in the field of sociology increased over the last two decades. Blockmodeling of co-authorship networks in sociology has shown that the sociologists who are not systematically tied to strongly connected and well-established research groups produce the most excellent scientific publications in their field.
Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.
In this paper we discuss the limits and potentials of bibliometric mapping based on a specific co-word analysis. The subject area is neural network research. Our approach is a simulation of expert assessment by offering the reader a narrative of the field which can be used as background information when reading the bibliometric maps. The central issue in the applicability of bibliometric maps is whether these maps may supply additional intelligence to users. In other words, whether such a bibliometric tool has an epistemological value, in the sense that it ecriches existing knowledge by supplying unexpected relations between specific pieces of knowledge (synthetic value) or by supplying unexpected problems (creative value). We argue that sophisticated bibliometric mapping techniques are indeed valuable for open new avenues to study science as a self-organizing system in the form of a neural network like structure of which the bibliometric map is a first-order aproximation. In that sense, this paper deals with the neural net of neural network research as our bibliometric techniques in fact mimic a connectionistic approach.
To analyse developments of scientific fields, scientometrics provides useful tools, provided one is prepared to take the content of scientific articles into account. Such cognitive scientometrics is illustrated by using as data a ten-year period of articles from a biotechnology core journal. After coding with key-words, the relations between articles are brought out by co-word analysis. Maps of the field are given, showing connections between areas and their change over time, and with respect to the institutions in which research is performed. In addition, other approaches are explored, including an indicator of theoretical level of bodies of articles.
A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together. The co-citation frequency of two scientific papers can be determined by comparing lists of citing documents in the Science Citation Index and counting identical entries. Networks of co-cited papers can be generated for specific scientific specialties, and an example is drawn from the literature of particle physics. Co-citation patterns are found to differ significantly from bibliographic coupling patterns, but to agree generally with patterns of direct citation. Clusters of co-cited papers provide a new way to study the specialty structure of science. They may provide a new approach to indexing and to the creation of SDI profiles.
We combine two seemingly distinct perspectives regarding the modeling of network dynamics. One perspective is found in the
work of physicists and mathematicians who formally introduced the small world model and the mechanism of preferential attachment.
The other perspective is sociological and focuses on the process of cumulative advantage and considers the agency of individual
actors in a network. We test hypotheses, based on work drawn from these perspectives, regarding the structure and dynamics
of scientific collaboration networks. The data we use are for four scientific disciplines in the Slovene system of science.
The results deal with the overall topology of these networks and specific processes that generate them. The two perspectives
can be joined to mutual benefit. Within this combined approach, the presence of small-world structures was confirmed. However
preferential attachment is far more complex than advocates of a single autonomous mechanism claim.
KeywordsScientific collaboration–Co-authorship network–Bibliometry–Longitudinal network analysis–Small world–Preferential attachment–Stochastic actor based model
This paper presents a quantitative performance analysis of two different approaches to the lemmatization of the Czech text
data. The first one is based on manually prepared dictionary of lemmas and set of derivation rules while the second one is
based on automatic inference of the dictionary and the rules from training data. The comparison is done by evaluating the
mean Generalized Average Precision (mGAP) measure of the lemmatized documents and search queries in the set of information
retrieval (IR) experiments. Such method is suitable for efficient and rather reliable comparison of the lemmatization performance
since a correct lemmatization has proven to be crucial for IR effectiveness in highly inflected languages. Moreover, the proposed
indirect comparison of the lemmatizers circumvents the need for manually lemmatized test data which are hard to obtain and
also face the problem of incompatible sets of lemmas across different systems.
One important theoretical focus in community informatics is based on the convergence of two established bodies of theory, social networks and social capital. First we summarize them both. Then we define community informatics and explore its origins. Finally, we review a group of community informatics studies which frame their analyses in either social capital or social network theory. How the frames are constructed focuses each study on either technological change or historical continuity. Taken together, the studies suggest that in fact both of these are necessary for local communities both to initiate and to sustain the use of information technologies.
The vast improvement in information access is not the only
advantage resulting from the increasing percentage of hyperlinked human
knowledge available on the Web. Additionally, much potential exists for
analyzing interests and relationships within science and society.
However, the Web's decentralized and unorganized nature hampers content
analysis. Millions of individuals operating independently and having a
variety of backgrounds, knowledge, goals and cultures author the
information on the Web. Despite the Web's decentralized, unorganized,
and heterogeneous nature, our work shows that the Web self-organizes and
its link structure allows efficient identification of communities. This
self-organization is significant because no central authority or process
governs the formation and structure of hyperlinks
We propose a simple method to extract the community structure of large networks. Our
method is a heuristic method that is based on modularity optimization. It is shown to
outperform all other known community detection methods in terms of computation time.
Moreover, the quality of the communities detected is very good, as measured by the
so-called modularity. This is shown first by identifying language communities in a Belgian
mobile phone network of 2 million customers and by analysing a web graph of 118 million
nodes and more than one billion links. The accuracy of our algorithm is also verified on ad
hoc modular networks.
This empirical research demonstrates the effectiveness of content analysis to map the research literature of the software engineering discipline. The results suggest that certain research themes in software engineering have remained constant, but with changing thrusts. Other themes have arisen, matured, and then faded as major research topics, while still others seem transient or immature. Co-word analysis is the specific technique used. This methodology identifies associations among publication descriptors (indexing terms) from the ACM Computing Classification System and produces networks of descriptors that reveal these underlying patterns. This methodology is applicable to other domains with a supporting corpus of textual data. While this study utilizes index terms from a fixed taxonomy, that restriction is not inherent; the descriptors can be generated from the corpus. Hence, co-word analysis and the supporting software tools employed here can provide unique insights into any discipline's evolution.
The paper investigates interdisciplinarity of scientific fields based on graph of collaboration between the researchers. A new measure for interdisciplinarity is proposed that takes into account graph content and structure. Similarity between science categories is estimated based on text similarity between their descriptions. The proposed new measure is applied in exploratory analysis of research community in Slovenia. We found that Biotechnology and Natural sciences are the most interdisciplinary in their publications and collaborations on research projects. In addition evolution of interdisciplinarity of scientific fields in Slovenia is observed, showing that over the last decade interdisciplinarity increases the fastest in Medical sciences mainly due to collaborations with Natural and Technical sciences.
Social structures are defined by their parameters--the criteria underlying the differentiation among people and governing social interaction, such as sex, race, socioeconomic status, and power. The analysis of various forms of differentiation, their interrelations, and their implications for integration and change is the distinctive task of sociology. Two generic types of differentiation are heterogeneity and status inequality. Nominal parameters divide people into subgroups and engender heterogeneity. Graduated parameters differentiate people in terms of status rankings and engender inequality. The macrosocial integration of the diverse groups in modern society rests on its multiform heterogeneity resulting from many crosscutting parameters. For although heterogeneity entails barriers to social intercourse multiform heterogeneity undermines these barriers and creates structural constraints to establish intergroup relations. Crosscutting lines of differentiation thus foster processes of social integration, and they also foster processes of recurrent change. Strongly interrelated parameters impede these processes of integration and adjustment, however. (Such relationships between parameters--for example, between the occupation and income of individuals--must not be confused with the relationships between forms of differentiation--for example, between the division of labor and income inequality in societies.) Pronounced correlations of parameters reveal a consolidated status structure, which intensifies inequalities and discourages intergroup relations and gradual change. The growing concentration of resources and powers in large organizations and their top executives poses a serious threat of structural consolidation in contemporary society.
In the paper, we apply small world complex network theory to analyze scientific research in the field of service innovation, and discover its research focuses. Our study considers the key words and subject categories of the publications as actors to map keyword co-occurrence network and subject category co-occurrence network, and compare them with their corresponding random binary networks to judge whether these complex networks have the characteristics of small world network, in order to find the hot issues in the field by the small world network analysis. We discuss the knowledge structure in the field through analyzing 437 papers that were searched from Web of Science database over the period 1992–2011. We find that case study, service industry, service quality, market orientation, new product development, and knowledge management were the most popular keywords of the field, and also show the dynamic development of the research focuses in recent 10 years. The researchers who made most contribution in a certain field are also found out. It is concluded that there were more researchers who did investigation about service innovation in the category of Business and Economics, Engineering, Public Administration, Operations Research and Management Science, and Computer Science than those in other categories. The study suggests a quantitative method to analyze trends of scientific research in a certain field, and presents some directions of research mainstream to the researchers who may be interested in the service innovation.
A classic problem common to sociology and other social sciences revolves around how people make decisions. Some recent approaches start with and revise an individually focused, rational action framework. While this orientation to building transdisciplinary, multilevel models provides many insights, it fails to capture essential features of social life. The social organization strategy (SOS) framework presented in this article offers a complementary approach to social action in general and decision making in particular. This orientation, a network and event-centered counterpart to rational choice, rests on fundamental principles that distinguish the discipline of sociology: social interaction is the basis of social life, and social networks provide the mechanism (interaction) through which individuals learn about, come to understand, and attempt to handle difficulties. This approach shifts the focus from individual "choice" to socially constructed patterns of decisions, including consultation with others. Utilization research in medical sociology serves as a case for reviewing theoretical approaches to decision making and provides the background necessary to a theoretical exposition of the SOS approach using data from the National Survey of Access to Medical Care (1975-76). The results support the utility of pursuing the SOS framework.
In this paper, we will study the field through the problematic network built by scientific articles, using actor-network theory (and consequently coword analysis) as a model for scientific knowledge (regarded as a social process) growth. Scientometrics is an hybrid field made of invisible college and a lot of users, thus controlled by both scientific research and final uses. Coword analysis gives the same weight to all articles, cited or not, and consequently computes the interaction network within all kind of authors. According to already described network properties of scientific interaction, coword analysis describes the dynamic of the field in accordance with what has been observed, and suggest forecast for the future.
The specialty of collagen research is tracked over a ten year period, 1970–1979, using the methodology of co-citation cluster strings. Independently obtained annual clusters are linked together over time by the percentage of highly cited documents countinuing from year to year. All inter-year links are clustered by single-linkage to form the strings, one of which corresponds to the collagen specialty. Maps of the individual year clusters within the string reveal an alternating pattern of expansion/innovation followed by contraction/consolidation. At the same time the subject focus of research gradually shifts. The institutional affiliation and funding sources for highly cited documents show a trend from early dominance by a few institutions and sources to a multiplicity and collaboration of centers and sources later on, due in part to the migration of researchers from an initially dominant institution.
The method of co-citation analysis is used to build citation networks in information science. As data base the first 13 volumes (1961–1973) of the leading Soviet journal in the field (Nauchno-tekhnicheskaya Informatsiya) were used. The results reveal the topical structure of information science, the communities of authors and the names of single leading scientists. The evaluation of scientists' work is based on two measures: productivity (with or without co-authorship) and popularity (popularity of authors and popularity of papers).
The goal of this paper is to show how co-word analysis techniques can be used to study interactions between academic and technological research. It is based upon a systematic content analysis of publications in the polymer science field over a period of 15 years. The results concern a.) the evolution of research in different subject areas and the patterns of their interaction; b.) a description of subject area life cycles; c.) an analysis of research trajectories given factors of stability and change in a research network; d.) the need to use both science push and technology pull theories to explain the interaction dynamics of a research field. The co-word techniques developed in this paper should help to build a bridge between research in scientometrics and work underway to better understand the economics of innovation.
This is the Guest Editor's introduction to the Special Issue on “Science of Science: Conceptualizations and Models of Science”, Journal of Informetrics. The introduction discusses challenges towards a theoretically grounded and practically useful science of science. It provides a brief chronological review of relevant work and argues for (1) the development of common frameworks for the comparison and combination of existing approaches, theories, laws, and measurements, (2) the combination of quantitative and qualitative studies of science, and (3) the operationalization of theoretical concepts in terms of measurement and empirical evidence. Next, three visual conceptualizations of science are discussed and compared. Each of them provides a framework for the comparison and combination of existing works, means to combine quantitative and qualitative data, and helps to operationalize and communicate theoretical concepts using empirical data. Last but not least, the contributions of and interlinkages among the papers included in this issue are discussed.
We study the evolution of Slovenia’s scientific collaboration network from 1960 till present with a yearly resolution. For each year the network was constructed from publication records of Slovene scientists, whereby two were connected if, up to the given year inclusive, they have coauthored at least one paper together. Starting with no more than 30 scientists with an average of 1.5 collaborators in the year 1960, the network to date consists of 7380 individuals that, on average, have 10.7 collaborators. We show that, in spite of the broad myriad of research fields covered, the networks form “small worlds” and that indeed the average path between any pair of scientists scales logarithmically with size after the largest component becomes large enough. Moreover, we show that the network growth is governed by near-liner preferential attachment, giving rise to a log-normal distribution of collaborators per author, and that the average starting year is roughly inversely proportional to the number of collaborators eventually acquired. Understandably, not all that became active early have till now gathered many collaborators. We also give results for the clustering coefficient and the diameter of the network over time, and compare our conclusions with those reported previously.
A bibliometric analysis was applied in this work to evaluate global scientific production of geographic information system (GIS) papers from 1997 to 2006 in any journal of all the subject categories of the Science Citation Index compiled by Institute for Scientific Information (ISI), Philadelphia, USA. ‘GIS’ and ‘geographic information system’ were used as keywords to search parts of titles, abstracts, or keywords. The published output analysis showed that GIS research steadily increased over the past 10 years and the annual paper production in 2006 was about three times 1997s paper production. There are clear distinctions among author keywords used in publications from the five most productive countries (USA, UK, Canada, Germany and China) in GIS research. Bibliometric methods could quantitatively characterize the development of global scientific production in a specific research field. The analytical results eventually provide several key findings.
The aim of this study is to map the intellectual structure of the field of Information Retrieval (IR) during the period of 1987–1997. Co-word analysis was employed to reveal patterns and trends in the IR field by measuring the association strengths of terms representative of relevant publications or other texts produced in IR field. Data were collected from Science Citation Index (SCI) and Social Science Citation Index (SSCI) for the period of 1987–1997. In addition to the keywords added by the SCI and SSCI databases, other important keywords were extracted from titles and abstracts manually. These keywords were further standardized using vocabulary control tools. In order to trace the dynamic changes of the IR field, the whole 11-year period was further separated into two consecutive periods: 1987–1991 and 1992–1997. The results show that the IR field has some established research themes and it also changes rapidly to embrace new themes.
Expertise Oriented Search (EOS) aims at providing comprehensive expertise analysis on data from distributed sources. It is
useful in many application domains, for example, finding experts on a given topic, detecting the confliction of interest between
researchers, and assigning reviewers to proposals. In this paper, we present the design and implementation of our expertise
oriented search system, Arnetminer (http://www.arnetminer.net). Arnetminer has gathered and integrated information about a half-million computer science researchers from the Web, including
their profiles and publications. Moreover, Arnetminer constructs a social network among these researchers through their co-authorship,
and utilizes this network information as well as the individual profiles to facilitate expertise oriented search tasks. In
particular, the co-authorship information is used both in ranking the expertise of individual researchers for a given topic
and in searching for associations between researchers. We have conducted initial experiments on Arnetminer. Our results demonstrate
that the proposed relevancy propagation expert finding method outperforms the method that only uses person local information,
and the proposed two-stage association search on a large-scale social network is order of magnitude faster than the baseline
method.
SUMMARY We present a modification of the spring-embedder model of Eades ( Congresses Numerantium, 42, 149-160, (1984)) for drawing undirected graphs with straight edges. Our heuristic strives for uniform edge lengths, and we develop it in analogy to forces in natural systems, for a simple, elegant, conceptually- intuitive, and efficient algorithm. Normally, graphs are depicted with their vertices as points in a plane and their edges as line or curve segments connecting those points. There are different styles of representation, suited to different types of graphs or different purposes of presentation. We concentrate on the most general class of graphs: undirected graphs, drawn with straight edges. In this paper, we introduce an algor- ithm that attempts to produce aesthetically-pleasing, two-dimensional pictures of graphs by doing simplified simulations of physical systems. We are concerned with drawing undirected graphs according to some generally accepted aesthetic criteria: 2
Part I. Introduction: Networks, Relations, and Structure: 1. Relations and networks in the social and behavioral sciences 2. Social network data: collection and application Part II. Mathematical Representations of Social Networks: 3. Notation 4. Graphs and matrixes Part III. Structural and Locational Properties: 5. Centrality, prestige, and related actor and group measures 6. Structural balance, clusterability, and transitivity 7. Cohesive subgroups 8. Affiliations, co-memberships, and overlapping subgroups Part IV. Roles and Positions: 9. Structural equivalence 10. Blockmodels 11. Relational algebras 12. Network positions and roles Part V. Dyadic and Triadic Methods: 13. Dyads 14. Triads Part VI. Statistical Dyadic Interaction Models: 15. Statistical analysis of single relational networks 16. Stochastic blockmodels and goodness-of-fit indices Part VII. Epilogue: 17. Future directions.
This paper reports on a bibliometric analysis of keywords in the literature on ethics and dementia during the period 1980-2000.
Keywords were drawn from titles, abstracts and keyword fields of 14 bibliographic databases and clustered in to 19 categories. These categories were then examined for their frequency and co-occurrences. The strength of relationships between these categories is mapped using the metaphor of the 'night sky' showing constellations of issues and changes over time.
Four categories appear consistently and frequently in the literature: professional care, end-of-life issues, decision-making and treatment. Other issues come and go (such as quality-of-life issues) while others appear to respond to outside events (e.g. feeding issues). The research literature is based predominantly on surveys or studies soliciting responses to predefined issues. Little research has been undertaken to establish the range of ethical issues for either family members or professionals.
We discuss the domination of the literature by four categories of ethical issues, the new and emerging areas of ethical interest and those areas that are triggered by external events such as legal cases. We also discuss some of the limitations of the study and note some omissions in the literature.
During the period 1980-2000 the research literature has been dominated by surveys and studies soliciting views on predefined issues with relatively few in-depth, open-ended qualitative studies.
Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the link prediction problem, and develop approaches to link prediction based on measures for analyzing the "proximity" of nodes in a network. Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
Main page”, available at: www.gutenberg.org/wiki/Main_Page
- Project Gutenberg
The neural net of neural network research – an exercise in bibliometric mapping