A quantitative exploration on reasons for citing articles from the perspective of cited authors

Citation is regarded as one of the “norms of science” (Merton in Am Sociol Rev 22(6):635–659, 1957) and is deeply researched by the field of scientometrics. The motivations authors have for citing one another are considered significant and have been the subject of extensive qualitative research such as content analysis, questionnaires, and interviews of citing authors. However, the existing qualitative studies have covered a limited number of samples. To expand the dataset, this paper proposes a quantitative method applied to detecting citation reasons from the angle of citation networks and the attributes of cited authors, including their publication count (the number of single-authored publications, collaborative and first-authored publications as well as collaborative but non-first-authored publications, and number of whole publications), citation count, research topic interests, and gender. By applying the Exponential Random Graph Models (ERGMs), the current study revealed that authors in the field of information retrieval tend to cite those with more single-authored, collaborative and first-authored, and collaborative but not first-authored publications. Besides, in this field, the number of publications, similar topical domains, and same gender are proven to be significantly favorable in selecting references in our experiment.     

Choosing the right collaboration partner for innovation: a framework based on topic analysis and link prediction

Selecting the right collaboration partner is one of the most important contributors to success in collaborative innovation. Accordingly, numerous methods for selecting an appropriate partner have been developed to guide would-be collaborators in their search. Most rely on bibliographic information, which may be easier for that data is readily available and relatively normalized. However, with the benefit of today’s text mining and fusion techniques, it is possible to mine the content of papers and patents so as to result in far more nuanced and advantageous choices. In this article, we explore how to select partners for collaborative innovation by combining the characteristics of the authors of paper and patent documents as well as their content. Drawing on existing research, we developed a systematic framework that relies on topic analysis and link prediction. With a corpus of papers and patents assembled, the framework extracts correlated scientific and technological topics followed by a list of author institutions and a list of patentees. These organisations are parsed and evaluated using two indicators of innovation—capability and openness—to result in two separate ranked lists. Two integrated collaboration networks that include both author institutions and patentees are then built, and a link prediction method identifies missing links with a high likelihood of fruitful cooperation. A case study on hepatitis C virus research shows that the ranking procedure and the link prediction method can be used either together or separately to effectively identify collaborative innovation partners. Our results provide significant quantitative evidence for policymakers who are looking to foster cooperation between research institutions and/or high-tech enterprises. Our research may also serve as the basis for further in-depth research on collaborative innovation, R&D cooperation, and link prediction theories and methods.

     

Trend and efficiency analysis of co-authorship network

Although co-authorship in scientific research has a long history the analysis of co-authorship network to explore scientific collaboration among authors is a relatively new research area. Studies of current literature about co-authorship networks mostly give emphasis to understand patterns of scientific collaborations, to capture collaborative statistics, and to propose valid and reliable measures for identifying prominent author(s). However, there is no such study in the literature which conducts a longitudinal analysis of co-authorship networks. Using a dataset that spans over 20 years, this paper attempts to explore efficiency and trend of co-authorship networks. Two scientists are considered connected if they have co-authored a paper, and these types of connections between two scientists eventually constitute co-authorship networks. Co-authorship networks evolve among researchers over time in specific research domains as well as in interdisciplinary research areas. Scientists from diverse research areas and different geographical locations may participate in one specific co-authorship network whereas an individual scientist may belong to different co-authorship networks. In this paper, we study a longitudinal co-authorship network of a specific scientific research area. By applying approaches to analyze longitudinal network data, in addition to known methods and measures of current co-authorship literature, we explore a co-authorship network of a relatively young and emerging research discipline to understand its trend of evolution pattern and proximity of efficiency.     

Quantitative analysis of collaborative and mobility networks

This study proposes a quantitative analysis of researcher mobility (i.e. transfer from one institution to another) and collaborative networks on the basis of author background data extracted from biographical notes in scientific articles to identify connections that are not revealed via simple co-authorship analysis. Using a top-ranked journal in the field of computer vision, we create a layered network that describes various aspects of author backgrounds, demonstrating a geographical distribution of institutions. We classify networks according to various dimensions including authors, institutions and countries. The results of the quantitative analysis indicate that mobility networks extend beyond the typical collaborative networks describing institutional and international relationships. We also discuss sectoral collaboration considering the mobility networks. Our findings indicate a limitation of collaborative analysis based on bibliometric data and the importance of tracing researcher mobility within potential networks to identify the true nature of scientific collaboration.     

Research collaboration networks of two OIC nations: comparative study between Turkey and Malaysia in the field of ‘Energy Fuels’, 2009–2011

With the world in the midst of an energy crisis, recent research has placed considerable emphasis on harnessing renewable and sustainable energy while efficiently using fossil fuels. Researchers create and sustain academic societies as a result of social interactions. This study takes a social network perspective to understand researchers’ associations using two Organisation of Islamic Co-operation nations, Turkey and Malaysia, in the fast-developing field of ‘Energy Fuels’. The study found both similarities and differences in the scholarly networks of these two countries. The mean distance between the authors in the Turkey and Malaysia networks was 8.4 and 6.5, respectively, confirming the small world nature of these networks. The popularity, position, and prestige of the authors in the network, as determined through centrality measures, had a statistically significant effect on research performance. These measures, however, were far more correlated with the research performance of the authors in the Malaysia network than in the Turkey network. PageRank centrality was found to be the most efficient topological measure when it came to correlation with research performance. We used authors’ ‘degree’ to reach to the ‘core’ (‘Deg-Core’) of the network (in contrast to the K-Core method), which was found to capture more productive authors. A method to detect academic communities of productive authors by extracting motifs (large cliques) from the network is suggested. Finally, we visualize the cognitive structure of both countries using a 2-mode network representing research focus areas (RFAs) and prominent authors working in these RFAs.     

The influence of socialisation and absorptive capacity on buyer’s innovation performance

In contrast to prior literature, we hypothesise that socialisation with suppliers plays a key role in the success of buyer’s innovation programmes. Using the theoretical lens of social capital theory and knowledge-based view of a firm; we propose a framework of antecedents and consequences of socialisation. We use data from a large sample of firms in Australia to test our framework. We also corroborate our results with a small sample of qualitative case studies that were carried out in conjunction with the large-scale empirical study. Taken together, the results supported the claim of the importance of socialisation as well as absorptive capacity in influencing innovation performance of buyers. The results suggest that managers ought to consider socialisation as a mechanism to enhance collaborative competence which in turn helps innovation performance via tapping the potential of absorptive capacity of knowledge.     

Ten Lectures on Impact-Echo

During the last seven years various aspects of the impact-echo method for non-destructive testing of concrete structures were studied in great detail by the authors. This work was performed within the framework of the German collaborative research initiative FOR 384, “Non-destructive evaluation of concrete structures using acoustic and electromagnetic methods”, and was supported by the German National Science Foundation (Deutsche Forschungsgemeinschaft, DFG). During this period significant new and important results were obtained and well known facts were re-discussed from a different angle of view. It is the belief of the authors that most of the new and even some of the old facts are not well-established in the impact-echo community. The main aim of the present paper therefore is to summarize these important aspects of impact-echo in terms of ten short lectures. In doing so, we will not only present results of our own work but will also include contributions from other groups with significant relevance for the practical use of impact-echo in field tests.     

Blockmodeling of co-authorship networks in library and information science in Argentina: a case study

The paper introduces the use of blockmodeling in the micro-level study of the internal structure of co-authorship networks over time. Variations in scientific productivity and researcher or research group visibility were determined by observing authors?? role in the core-periphery structure and crossing this information with bibliometric data. Three techniques were applied to represent the structure of collaborative science: (1) the blockmodeling; (2) the Kamada-Kawai algorithm based on the similarities in co-authorships present in the documents analysed; (3) bibliometrics to determine output volume, impact and degree of collaboration from the bibliographic data drawn from publications. The goal was to determine the extent to which the use of these two complementary approaches, in conjunction with bibliometric data, provides greater insight into the structure and characteristics of a given field of scientific endeavour. The paper describes certain features of Pajek software and how it can be used to study research group composition, structure and dynamics. The approach combines bibliometric and social network analysis to explore scientific collaboration networks and monitor individual and group careers from new perspectives. Its application on a small-scale case study is intended as an example and can be used in other disciplines. It may be very useful for the appraisal of scientific developments.     

Knowledge integrators or weak links? An exploratory comparison of patenting researchers with their non-inventing peers in nano-science and technology

Summary Policy-makers in many countries emphasize the importance of non-publication output of university research. Increasingly, policies are pursued that attempt to encourage entrepreneurial activity in universities and public research institutes. Apart from generating spin-out companies, technology licensing, and collaborative research, attention is focused on patenting activities of researchers. Some analysts suggest that there is a trade-off between scholarly publication and patenting activity. This paper explores this relationship drawing on a data set of nanoscience publications and nanotechnology patents in three European countries. In particular, this study examines whether researchers who both publish and patent are more productive and more highly cited than their peers who concentrate on scholarly publication in communicating their research results. Furthermore, this study investigates the collaborative activity of inventor-authors and their position in their respective networks of scientific communication. The findings suggest that overall there seems to be no adverse relationship between publication and patenting activity, at least not in this area of science and technology. Patenting scientists appear to outperform their solely publishing, non-inventing peers in terms of publication counts and citation frequency. However, while they are considerably over-represented in the top performance class, the data indicates that inventor-authors may not occupy top positions within that group. An analysis of co-authorship links indicates that patenting authors can also play a prominent role within networks of scientific communication. The network maps also point to groups where inventor-authors occur frequently and others where this is not the case, which possibly reflects cognitive differences between sub-fields. Finally, the data indicates that inventor-authors account only for a marginal share of publishing scholars while they play a substantial role amongst inventors.     

Research collaboration in groups and networks: differences across academic fields

The purpose of this paper is to give a macro-picture of collaboration in research groups and networks across all academic fields in Norwegian research universities, and to examine the relative importance of membership in groups and networks for individual publication output. To our knowledge, this is a new approach, which may provide valuable information on collaborative patterns in a particular national system, but of clear relevance to other national university systems. At the system level, conducting research in groups and networks are equally important, but there are large differences between academic fields. The research group is clearly most important in the field of medicine and health, while undertaking research in an international network is most important in the natural sciences. Membership in a research group and active participation in international networks are likely to enhance publication productivity and the quality of research.     

The state of the art development of AHP (1979–2017): a literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions.     

A new approach to analyzing patterns of collaboration in co-authorship networks: mesoscopic analysis and interpretation

This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesoscopic level. We combine qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the application and value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we base our analysis on the observed modular structure of co-author networks. We interpret the clustering of authors into groups as bibliometric footprints of the basic collective units of knowledge production in a research specialty. We find two types of coauthor-linking patterns between author clusters that we interpret as representing two different forms of cooperative behavior, transfer-type connections due to career migrations or one-off services rendered, and stronger, dedicated inter-group collaboration. Hence the generic coauthor network of a research specialty can be understood as the overlay of two distinct types of cooperative networks between groups of authors publishing in a research specialty. We show how our analytic approach exposes field specific differences in the social organization of research.     

Feasibility of online collaborative voltage stability control of power systems

The authors present the results of feasibility study of a novel concept of power system online collaborative voltage stability control. Online collaboration between power system controllers is proposed in order to enhance their overall performance and efficiency to cope with the increasing operational uncertainty of modern power systems. The framework of the proposed online collaborative voltage stability control is first presented, which is based on the deployment of multi-agent systems and real-time communication for online collaborative control. Then, two of the most important issues in implementing the proposed online collaborative voltage stability control are addressed: (1) Error-tolerant communication protocol for fast information exchange among multiple intelligent agents; (2) Deployment of multi-agent systems by using graph theory to implement power system post-emergency control. Results of testing the proposed online collaborative voltage stability control in the case of the 10-machine 39-node New England power system are presented. Results of a feasibility study by means of a simulation are given that take into consideration low-probability cascading faults in the power system.     

Multiplexity,Growth Mechanisms and Structural Variety in Scientific Collaboration Networks

A substantial body of literature has recently been concerned with the structure and dynamics of the collaboration networks that underlie the production and dissemination of scientific knowledge. Despite the growing interest in these networks, relatively little emphasis has been placed on two broad areas of investigation: on the one hand, the interplay of the growth mechanisms underpinning the evolution of collaborative arrangements; on the other, the implications that the structure and multiplexity of these arrangements have on knowledge creation and diffusion. The articles in this Special Issue aim to bridge these gaps in the literature and, by embracing a variety of perspectives, contribute towards a better understanding of how collaboration networks originate, function, and evolve. This Introduction offers a theoretical and methodological framework for the articles here included. It begins by discussing problems of measurement of scientific collaboration, and goes on to examine the role that growth mechanisms, structural variety and multiplexity play in shaping the genesis and functioning of collaboration networks. In reviewing current and emerging research themes, the discussion will also identify promising research directions that will stimulate future work on collaboration networks in science and technology.     

Linking networks and plant roles: the impact of changing a plant role

Many manufacturing firms are expanding their global footprint to explore new opportunities for efficient and effective production. The strategic perspective on international manufacturing networks involves both the network level and the plant level. A key aspect is the relationship between the network and the role of plants. In this research, we investigate the relationship between the network and plant perspectives in international manufacturing networks. We use an embedded case study that includes five plants in two product networks over a period of three years. We analyse how changing the role of one plant affects the network as well as the roles of the other plants in the networks. We find that decisions on plant roles are, to a very high degree, network decisions and not decisions for individual plants. Based on the insights into the case study, we also develop a framework for mapping manufacturing networks, including market coverage, plant location and site competence.     

Collaboration networks and collaboration tools: a match for SMEs?

Global patterns of industrial production have resulted in relocation of industrial operations groups in an effort to create new markets for mass and customised mass production. The collaborative effort between these dispersed teams increases the likelihood of combining ideas and knowledge in novel ways. Internet technologies enable these virtual collaboration networks to seamlessly engage in discussions that demonstrate a richness of perspectives when it comes to problem-solving and innovative idea-exchange. Indeed, knowledge creation and harnessing collective knowledge are salient features of collaborative networks (CNs) and this is witnessed by a new interest in these entities. However, small and medium enterprises (SMEs) display a difficulty in partnering and collaborating in global networks, especially since their technological infrastructure may be lacking. Given the widespread adoption of collaborative technologies in social contexts, this research seeks to examine how such informal interactions are facilitated in SMEs through Web 2.0 tools. Specifically, this paper seeks to contribute to existing literature by examining how Web 2.0 affects the collaborative effort in two SME CNs; this study demonstrated that the collaboration effort is amplified when Web 2.0 tools are available. Other parameters such as trust in other members’ ability; perception of usefulness; and enhancement of collective knowledge are seen as supporting the CN mutuality. In addition, it brings together the three diverse research areas of collaborative networks, internet collaborative tools and psychological barriers and enablers.     

Elite Researchers in Ophthalmology: Aspects of Publishing Strategies,Collaboration and Multi-Disciplinarity

This study covers a ten-year period, 1990-1999, of the publishing careers of nine authors who appear in the top-20 most productive authors in the field of ophthalmology. In this paper we discuss findings from a study of the publishing careers of elite researchers in the field of ophthalmology. The paper highlights the extent and nature of the journals in which these elite researchers publish their work. Data derived from the study include indications of multidisciplinary involvement or 'work-space' interests, publication characteristics, and collaborative engagement with others. We provide insights into the workings of author productivity, characteristics of papers such as numbers per paper of pages, references, and authors, and initial findings about their collaboration patterns. These findings, showing (ir)regularities or patterns in publishing careers, may be of interest to researchers and practitioners because they provide a view that might not otherwise be apparent to the field or to authors themselves. This revised version was published online in June 2006 with corrections to the Cover Date.     

Assessing scientific collaboration through coauthorship and content sharing

Over the past decade there have been many investigations aimed at defining the role of scientists and research groups in their coauthorship networks. Starting from the assumptions of network analysis, in this work we propose an analytical definition of a collaboration potential between authors of scientific papers based on both coauthorships and content sharing. The collaboration potential can also be considered a useful tool to investigate the relationships between a single scientist and research groups, thus allowing for the identification of characteristic “types” of scientists (integrated, independent, etc.). We computed the collaboration potential for a set of authors belonging to research groups of an institute specialized in the field of Medical Genetics. The methods presented in the paper are rather general as they can be applied to compute a collaboration potential for a network of cooperating actors in every situation in which one can qualify the content of some activities and which of them are in common among the actors of the network.     

Inequality and collaboration patterns in Canadian nanotechnology: implications for pro-poor and gender-inclusive policy

Policymakers and scholars are increasingly concerned with how nanotechnology can reduce inequalities and provide benefits for disadvantaged and poor communities. This paper simultaneously addresses two concerns related to nanotechnology and equity: the lack of research and development focused on nanotechnology applications that benefit developing nations (pro-poor R&D) and the lack of women in nanotechnology fields. The paper focuses on Canada, an affluent country committed to both pro-poor and gender responsive policies. Social network analysis is used to examine the relationship between gender and collaboration patterns of authors and inventors whose work is related to pro-poor applications of nanotechnology. Findings reveal that female first-authored papers have a lower citation rate and are published in higher ranked journals compared to those papers first-authored by men. Nevertheless, when women are last or corresponding authors, their papers receive equal or higher citation rates and are published in lower or similar ranked journals. Women are as, or more, collaborative as their male peers in their co-authorship and co-inventorship networks. While the majority of male authors and male inventors collaborate exclusively with men, those involved in a mixed-gender team outperform male-only teams. Women, as both authors and inventors, are involved in more gender-balanced collaboration teams. The study calls for development and implementation of gender-related policies in Canada to increase the prevalence of female scientists in collaboration networks, and to support the participation of women in pro-poor areas.     

Collaboration patterns of Taiwanese scientific publications in various research areas

This paper employs bibliometric methods to observe collaboration patterns of scientific publications in biotechnology, information and computer technology, future energy, and nanotechnology among different institutions in Taiwan. The results show primary domestic and international collaborative patterns, the effect of collaborative papers on the world-wide average, collaborative networks, and the distribution of institutions on global map. The findings suggest that domestic collaboration in each area is higher in proportion than international collaboration. Biotechnology leads in both domestic and international collaborative percentage. Among cooperative benchmarking countries, the US and China are the main partners. Collaboration among research institutes and universities is the most frequent collaborative pattern in each area except biotechnology, which tends to occur between hospitals and universities. On average, international collaborative papers tend to have greater effect, except in nanotechnology. Academia Sinica collaborated frequently with foreign institutes in each research field. A further analysis on how each collaborative group forms is recommended, especially collaboration among the Triple-Helix relationships.