Comparative analysis of co-authorship networks considering authors' roles in collaboration: Differences between the theoretical and application areas

Summary Many studies have analyzed “direct” partnerships in co-authorship networks. On the other hand, the global network structure, including “indirect” links between researchers, has not yet been sufficiently studied. This study analyzes researchers' activities from the viewpoints considering their roles in the global structures of co-authorship networks, and compares the co-authorship networks between the theoretical and application areas in computer science. The modified HITS algorithm is used to calculate the two types of importance of researchers in co-authorship networks, i.e., the importance as the leader and that as the follower.     

Identity and publication in non-university settings: academic co-authorship and collaboration

Increased collaboration between researchers working in university, industry, and governmental settings is changing the landscape of academic science. Traditional models of the interaction between these sectors, such as the triple helix concept, draw clear distinctions between academic and non-academic settings and actors. This study surveyed scientists (n = 469) working outside of university settings who published articles indexed in the Web of Science about their modes of collaboration, perceptions about publishing, workplace characteristics, and information sources. We study the association between these variables, and use text analysis to examine the roles, duties, sites, topics, and workplace missions among non-university based authors. Our analysis shows that 72% of authors working in non-university settings who collaborate and publish with other scientists self-identify as academics. Furthermore, their work life resembles that of those working in university settings in that the majority report doing fundamental research in government research organizations and laboratories. Contrary to our initial hypothesis, this research suggests that peer-reviewed publications are much more dominated by non-university academics than we previously thought and that collaboration as co-authors on academic publications is not likely to be a primary conduit for the transfer of scientific knowledge between academe and industry.

     

Site co-link analysis applied to small networks: a new methodological approach

The method of co-link was proposed in 1996 and since then it has been applied in many Webometric studies. Its definition refers to “page co-link analysis”, as links are provided by URLs or pages. This paper presents a new methodological approach, a “site co-link analysis”, to investigate relations in small networks. The Oswaldo Cruz Foundation institutes were used as a case study. The results indicate that the number of co-links provided by sites led to an increase of 133% in the sample analyzed. In a cluster analysis, three clusters were formed mainly for thematic reasons and four institutes remained isolated.     

Modelling and measuring multilateral co-authorship in international scientific collaboration. Part I. Development of a new model using a series expansion approach

International co-operation has strongly intensified during the last decades owing to rapid developments in scientific communication. Economic, political, and intra-scientific factors also strongly influence international collaboration links among individual countries. Obviously research results of international scientific co-operation are reflected in the documented scientific communication as international co-authorship links in scientific publications. Most bibliometric studies on this issue pertain to the share of international co-authored papers in national publication output and their impact on national and international research, or to the analysis and mapping of the structure of collaboration links. The present study attempts to develop a model to measure and analyse the extent of multilateral international co-authorship links. A new indicator, the Multilateral Collaboration Index (ρ) is introduced and analysed as a function of the share of internationally co-authored papers (f). Based onf a series expansion approach is applied that can be considered an extension of a fractionation model byNederhof andMoed and allows classifying the extent of multilateral links both among science fields and among individual countries. The paper is concluded by a first attempt to estimate the errors involved in our approach.     

Bibliometric indicators of Indian research collaboration patterns: A correspondence analysis

International collaboration is becoming an increasingly significant issue in science. During the last few years, a large number of bibliometric studies of co-authorships have been reported. Mostly, these studies have concentrated on country-to-country collaboration, revealing general patterns of interaction. In this study we analyze international collaborative patterns as indicated in the Indian publications by tracking out multi author publications as given in Science Citation Index (SCI) database. Correspondence analysis is used for analysis and interpretation of the results. According to correspondence analysis of the data set, Physics, Chemistry, Clinical medicine are the first, second and third largest subjects having international collaboration. USA, Italy, Germany, France, England are the top five countries with which India is collaborating. The data set shows an association between Physics and Italy, Switzerland, Algeria, Finland, South Korea, Russia, Netherlands contrasting an association between Biology & Biochemistry, Immunology, Ecology & Environment, Geosciences, Multidisciplinary subjects and England, Japan, Canada. It also shows an association between Agriculture and Philippines, Canada, Denmark in contrast to an association between Chemistry and Malaysia, Germany, France. An association between Clinical medicine, Astrophysics and England, Sweden, USA, New Zealand in contrast to an association between Agriculture and Canada, Philippines, Denmark is shown. An association between Engineering, Mathematics, Computer Science, Neuroscience and Singapore, Canada, USA in contrast to an association between Chemistry, Astrophysics and Malaysia, Spain is shown. This association of collaborating countries and disciplines almost tallies with the publication productivity of these countries in different disciplines.     

Structure and evolution of Indian physics co-authorship networks

We trace the evolution of Indian physics community from 1919 to 2013 by analyzing the co-authorship network constructed from papers published by authors in India in American Physical Society (APS) journals. We make inferences on India’s contribution to different branches of Physics and identify the most influential Indian physicists at different time periods. The relative contribution of India to global physics publication (research) and its variation across subfields of physics is assessed. We extract the changing collaboration pattern of authors between Indian physicists through various network measures. We study the evolution of Indian physics communities and trace the mean life and stationarity of communities by size in different APS journals. We map the transition of authors between communities of different sizes from 1970 to 2013, capturing their birth, growth, merger and collapse. We find that Indian–Foreign collaborations are increasing at a faster pace compared to the Indian–Indian. We observe that the degree distribution of Indian collaboration networks follows the power law, with distinct patterns between Physical Review A, B and E, and high energy physics journals Physical Review C and D, and Physical Review Letters. In almost every measure, we observe strong structural differences between low-energy and high-energy physics journals.

     

Detecting,identifying and visualizing research groups in co-authorship networks

The present paper proposes a method for detecting, identifying and visualizing research groups. The data used refer to nine Carlos III University of Madrid departments, while the findings for the Communication Technologies Department illustrate the method. Structural analysis was used to generate co-authorship networks. Research groups were identified on the basis of factorial analysis of the raw data matrix and similarities in the choice of co-authors. The resulting networks distinguished the researchers participating in the intra-departmental network from those not involved and identified the existing research groups. Fields of research were characterized by the Journal of Citation Report subject category assigned to the bibliographic references cited in the papers written by the author-factors. The results, i.e., the graphic displays of the structures of the socio-centric and co-authorship networks and the strategies underlying collaboration among researchers, were later discussed with the members of the departments analyzed. The paper constitutes a starting point for understanding and characterizing networking within research institutions.     

A novel approach for analyzing severe crash patterns on multilane highways

This study presents a novel approach for analysis of patterns in severe crashes that occur on mid-block segments of multilane highways with partially limited access. A within stratum matched crash vs. non-crash classification approach is adopted towards that end. Under this approach crashes serve as units of analysis and it does not require aggregation of crash data over arterial segments of arbitrary lengths. Also, the proposed approach does not use information on non-severe crashes and hence is not affected by under-reporting of the minor crashes. Random samples of time, day of week, and location (i.e., milepost) combinations were collected for multilane arterials in the state of Florida and matched with severe crashes from the corresponding corridor to form matched strata consisting of severe crash and non-crash cases. For these cases, geometric design/roadside and traffic characteristics were derived based on the corresponding milepost locations. Four groups of crashes, severe rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes, on multilane arterials segments were compared separately to the non-crash cases. Severe lane-change related crashes may primarily be attributed to exposure while single-vehicle crashes and pedestrian crashes have no significant relationship with the ADT (Average Daily Traffic). For severe rear-end crashes speed limit, ADT, K-factor, time of day/day of week, median type, pavement condition, and presence of horizontal curvature were significant factors. The proposed approach uses general roadway characteristics as independent variables rather than event-specific information (i.e., crash characteristics such as driver/vehicle details); it has the potential to fit within a safety evaluation framework for arterial segments.     

Collaboration uncovered: Exploring the adequacy of measuring university-industry collaboration through co-authorship and funding

Summary Analysing co-authored publications has become the standard way to measure research collaborations. At the same time bibliometric researchers have advised that co-authorship based indicators should be handled with care as a source of evidence on actual scientific collaboration. The aim of this study is to assess how well university-industry collaborations can be identified and described using co-authorship data. This is done through a comparison of co-authorship data with industrial funding to a medical university. In total 436 companies were identified through the two methods. Our results show that one third of the companies that have provided funding to the university had not co-authored any publications with the university. Further, the funding indicator identified only 16% of the companies that had co-authored publications. Thus, both co-authorship and funding indicators provide incomplete results. We also observe a case of conflicting trends between funding and co-authorship indicators. We conclude that uncritical use of the two indicators may lead to misinterpretation of the development of collaborations and thus provide incorrect data for decision-making.     

Evolutionary dynamics of scientific collaboration networks: multi-levels and cross-time analysis

Several studies exist which use scientific literature for comparing scientific activities (e.g., productivity, and collaboration). In this study, using co-authorship data over the last 40 years, we present the evolutionary dynamics of multi level (i.e., individual, institutional and national) collaboration networks for exploring the emergence of collaborations in the research field of “steel structures”. The collaboration network of scientists in the field has been analyzed using author affiliations extracted from Scopus between 1970 and 2009. We have studied collaboration distribution networks at the micro-, meso- and macro-levels for the 40 years. We compared and analyzed a number of properties of these networks (i.e., density, centrality measures, the giant component and clustering coefficient) for presenting a longitudinal analysis and statistical validation of the evolutionary dynamics of “steel structures” collaboration networks. At all levels, the scientific collaborations network structures were central considering the closeness centralization while betweenness and degree centralization were much lower. In general networks density, connectedness, centralization and clustering coefficient were highest in marco-level and decreasing as the network size grow to the lowest in micro-level. We also find that the average distance between countries about two and institutes five and for authors eight meaning that only about eight steps are necessary to get from one randomly chosen author to another.     

A multicriteria approach to timeout collaboration protocol

This paper presents a multicriteria approach to exploring the properties of timeout collaboration protocol with different timeout thresholds in general testing environments. This is formulated as a discrete multiple criteria optimisation problem by choosing five representative timeout thresholds as alternatives with five common performance measures of production systems. The PROMETHEE method is adopted to deal with this multicriteria problem. The divide-and-label algorithm is developed to rank all the alternatives with the overall intensity of their performance, by using multiple valued outranking graphs from the PROMETHEE with multiple replications. It is shown that two extreme timeout thresholds, T ₀ = 0 and ∞, are efficient over multiple criteria in almost all cases. The divide-and-label algorithm is a very efficient approach to overcome the limitations of the PROMETHEE algorithm and Belz and Mertens's procedure with multiple criteria and replications.     

A new approach to dynamic fuzzy modeling of genetic regulatory networks

In this paper, the dynamic fuzzy modeling approach is applied for modeling genetic regulatory networks from gene expression data. The parameters of the dynamic fuzzy model and the optimal number of fuzzy rules for the fuzzy gene network can be obtained via the proposed modeling approach from the measured gene expression data. One of the main features of the proposed approach is that the prior qualitative knowledge on the network structure can be easily incorporated in the proposed identification algorithm, so that the faster learning convergence of the algorithm can be achieved. Two sets of data, one the synthetic data, and the other the experimental SOS DNA repair network data with structural knowledge, have been used to validate the proposed modeling approach. It is shown that the proposed approach is effective in modeling genetic regulatory networks.     

Social dynamics of research collaboration: norms,practices, and ethical issues in determining co-authorship rights

Co-authorship has become common practice in most science and engineering disciplines and, with the growth of co-authoring, has come a fragmentation of norms and practices, some of them discipline-based, some institution-based. It becomes increasingly important to understand these practices, in part to reduce the likelihood of misunderstanding in collaborations among authors from different disciplines and fields. Moreover, there is also evidence of widespread satisfaction with collaborative and co-authoring experiences. In some cases the dissatisfactions are more in the realm of bruised feelings and miscommunication but in others there is clear exploitation and even legal disputes about, for example, intellectual property. Our paper is part of a multiyear study funded by the U.S. National Science Foundation (NSF) and draws its data from a representative national survey of scientists working in 108 Carnegie Doctoral/Research Universities—Very High Research Activity (n = 641). The paper tests hypotheses about the determinants of collaboration effectiveness. Results indicate that having an explicit discussion about co-authorship reduces the odds of a bad collaboration on a recent scholarly article. Having co-authors from different universities also reduces the odds of a bad collaboration, while large numbers of co-authors have the reverse effect. The results shed some systematic, empirical light on research collaboration practices, including not only norms and business-as-usual, but also routinely bad collaborations.     

A new model of scientific collaboration part 2. Collaboration patterns in Indian medicine

Collaboration in science has become a prevailing trend and it will be worthwhile to study the patterns of co-authorships in scientific research. In this study a three-dimensional behavioural pattern of Indian medicinal co-authorship network is presented. The high evenness of this pattern has caused us to carry out a non-linear regression analysis. The pattern of Indian Medicinal coauthorships can be described by the same non-linear mathematical function that describes the behavioural patterns of international medicine co-authorship networks and networks of other scientific disciplines. The following question has arise: Is there a general validity of this function in co-authorship networks?     

International collaboration in scientific research in Vietnam: an analysis of patterns and impact

Scientometrics - The present study sought to examine the trend and impact of international collaboration in scientific research in Vietnam during the period after the introduction of the a reform...     

Powers in nonsinusoidal networks: their interpretation, analysis,and measurement

A nonlinear or periodically time-variant load sometimes has to be considered not as the receiver, but as the source of energy, at least for some harmonic frequencies. This can be explained in terms of its equivalent circuit, usually composed of passive elements and harmonic sources which make the power phenomena in such a circuit much more complex than in a linear circuit. The necessity of comprehension of these phenomena stems from the fact that they determine the efficiency of the power transmission and the possibility of power factor improvement. They also affect the energy accounts. A method is suggested for the apparent power decomposition into components related to current components of distinctively different physical interpretation. A digital analyzer for measuring these powers is described