Author Collaboration Networks Research Articles

Two decades of Wikipedia research: a PubMed bibliometric network analysis

PurposeThis paper aims to examine the structure and dynamics of scholarly publications dealing with Wikipedia. The research also aims to investigate how such research evolved since its launch in 2001.Design/methodology/approachWikipedia has grown to be the biggest online encyclopedia in terms of comprehensiveness, reach and coverage. Based on 1,040 PubMed Wikipedia documents written by 5,280 authors over two decades (2001–2021), this paper conducts a bibliometric review of the intellectual structure of scholarly publications dealing with Wikipedia.FindingsResults show that annual scholarly publications on Wikipedia growth rate is 13.26. Major outlets publishing Wikipedia’s research are PloS One, the Journal of Medical Internet Research, Nucleic Acids Research, Studies in Health Technology and Informatics, Bioinformatics and the International Journal of Medical Informatics. Results also show that the author collaboration network is very sparse, signifying rather negligible collaboration among the authors. Furthermore, results reveal that the Wikipedia research institutions’ collaboration network reflects what is sometimes termed Wikipedia’s “North-South divide,” indicating limited collaboration between rich and poor nations’ institutions. Finally, the multiple correspondence analysis applied to obtain the Wikipedia research conceptual map and its intellectual structure reveals the intellectual thrust and the diversity of the scholarly publications dealing with Wikipedia.Originality/valueTo the best of the author’s knowledge, this research represents the first application of bibliometric methods to investigate two decades of scholarly publications dealing with Wikipedia based on the PubMed database.

Resilient City: A Bibliometric Analysis and Visualization

Resilient city has attracted global attentions as a new concept for cities to deal with risks and challenges in recent years. Numerous researchers have successively conducted in-depth studies on the resilient city from different perspectives. To acquire an overview of resilient city and grasp the current research hotspots, a bibliometric analysis and visualization of the past decade of research on the resilient city was made. The data were collected from 1249 articles published in the Web of Science database from 2010 to 2019. As the widely used bibliometric analysis tools, CiteSpace and VOSviewer were adopted in this study. The temporal distribution of resilient city research, including annual publication outputs and high-cited papers, was symmetrically analyzed. Then, the spatial distribution of resilient city research, including countries, categories, institutions, co-citation journals, author collaboration network, and author co-citation network, was investigated. Hot topics and evolution trends of resilient city were revealed. The results show that the research of resilient city experienced three periods, namely, germination, rapid diffusion, and reflection and innovation periods. Current research focuses on four aspects, including psychological resilience at the microcommunity and group levels, assessment of urban disaster resilience, multiple theoretical frameworks of urban resilience, and urban resilience promotion strategy. Therefore, this study helps scholars and practitioners to gain a comprehensive understanding of the current research progress and evolution trends of the resilient city field.

Research cooperations of blockchain: toward the view of complexity network

Blockchain has critically influence on the implementations with respect to various territories. Recently, a flurry of papers, related to blockchain, are published under such background. However, most of them focus on specific topic due to space limitations, which cannot meet a high-level analysis. In this paper, lots of papers concerning blockchain, smart contracts and bitcoins are collected as many as possible such that we can carry on a comprehensive analysis on blockchain. More specifically, we construct keyword and author collaboration networks after removing the unrelated and low-quality works. Then we delve into the characteristics of complex networks, such as degree distribution, betweeness and closeness. We further present the networks with the help of visual tools like Pajek. Some unconspicuous hot topics are uncovered, with the help of complex network. These topics can in turn push the cross-field development of block chain technology, which may promote social development.

Global scientific output trend for Akkermansia muciniphila research: a bibliometric and scientometric analysis

BackgroundAkkermansia muciniphila is an anaerobic bacterium residing in the healthy intestinal tract of host and its quantity has a negative correlation with various host diseases. This study for the first time provides a holistic bibliometric aspect of Akkermansi muciniphila research in the literature and shows the hot topic terms of these articles in any period of time.MethodsScopus database was selected to retrieve documents relevant to Akkermansia muciniphila in any language up to 2019. The bibliometric profile of Akkermansia muciniphila articles including subject area, year distribution, citations, institutions, journals, authors, and countries was systematically characterized and the collaboration networks of authors and countries as well as the burst detection algorithm of the words in the titles, abstracts and keywords were visualized.ResultsThere is a progressive growing trend in research on Akkermansia from 2004 to 2019 with a total of 566 articles during this period. Out of 353 original articles, there are 194 animal studies (155 studies on mice) and 112 human studies. Also, 65 various diseases were investigated in these studies. The most focused conditions are obesity (71 articles) and type2 diabetes (39 articles). The United States is the leading country on Akkermansia publications (n = 132), followed by China (n = 95). Frontiers in Microbiology is the most dominant journal with 23 Akkermansia publications. In addition, “cancer” is the hot topic of recent Akkermansia research.ConclusionAkkermansia research is of progressive interest during the last decade and the studies on this subject move towards its relationship with cancer and its promising effect on health.

Bibliometrics and Network Analysis of Cryptocurrency Research

Cryptocurrency, as an emerging social phenomenon, has attracted great research attentions and starts to form a new research area in the past decade. A thorough review of the existing cryptocurrency literatures helps us to understand the status-quo and the promising research future of this emerging field. This paper provides a systematic review of the cryptocurrency literatures by employing bibliometrics and network analysis methods. A total of 833 publications from Web of Science Core Collection and Scopus have been collected in the time period of January 2008 to June 2018. We examine the descriptive features, countries’ contributions and collaboration networks, author collaboration networks and reference co-citation networks to identify actors with significant influence in this field. The results show that cryptocurrency research is experiencing exponential growth, but scientific collaborations between different countries and authors are still insufficient. The intellectual bases of the cryptocurrency domain rest on the early-year literatures that provide fundamental understandings for cryptocurrency, and that bridge different research fields. The analysis indicates that the current research trend focuses on cryptocurrency market analysis incorporating market behaviors and trading characteristics.

Worldwide trends in the scientific production on rural depopulation, a bibliometric analysis using bibliometrix R-tool

The scientific production on rural depopulation has grown in recent years. However, a global picture of the research carried out on this topic does not exist. The aim of this study is to identify the worldwide trends in rural depopulation scientific production over time in the main levels of analysis: sources, authors and documents. A bibliometric analysis was developed to analyse a final sample of 1150 articles published between 1979 and 2018. In order to develop the analysis, bibliometrix R-Tool was used and the metadata of two databases (WoS and Scopus) was retrieved and merged. Results show two major areas of co-citation networks; a poor network of collaboration between countries with some highlighted interaction; an author collaboration network with close groups of knowledge and two main themes resulting from a co-word analysis. The main conclusion is that rural depopulation is not yet a solid field of research and the most important themes identified are related to specific geographical areas. However, international collaborations are growing, new trends appearing, and other related fields are expressing greater interest in rural depopulation, which could indicate the preceding stage to an eventual consolidation of the theme. This finding can assist future research in this or related fields by providing a worldwide overview of rural depopulation research over time.

Knowledge Mapping on Literature Research Progress of Human Thermal Comfort in buildings Based on Web of Science

This study focused on hot topics and front of thermal comfort in buildings by knowledge mapping of 577 research papers from 2009 to 2019 in the database of Web of Science as samples. CiteSpace software was used as the analyzing tool. The results showed the trend of the published researches on thermal comfort by analyzing high-frequency co-occurrence keywords and the keywords’ frequency variation. The results also showed that the researches on thermal comfort about health had increased rapidly in recent years. Moreover, the institutions and authors involved in healthy indoor thermal environment were mostly from economically developed countries or regions. However, the productive author collaboration network had not been formed yet. Improving environmental quality is the forefront of current researches. The research of indoor environmental quality based on health may be a hot topic in the future.

Research on political instability, uncertainty and risk during 1953–2019: a scientometric review

We are now living in an integrated world full of abrupt political events and socio-political uncertainty. A comprehensive scientometric review in this aspect is useful but lacked in the existing literature. This paper fills the void by using VOSviewer and CiteSpace to systematically analyze the 4200 papers on “political instability”, “political uncertainty” and “political risk” during 1953–2019 from Web of Science Core Collection. We present the annual distribution of papers, the related disciplines, the mainstream journals, hot topics, references with the strongest citation bursts, recent publications with transformative potentials, as well as the collaboration networks of authors, organizations and countries. The hot spots include (1) the causes and impact of political instability, (2) the relationship among political uncertainty, energy price and macroeconomic/financial factors, and (3) the determinants of foreign direct investments. Rangan Gupta from University of Pretoria in South Africa has the most publications in this field, while Witold J Henisz from University of Pennsylvania in the USA has the most citations. As the first endeavor to do comparative study of easily confused terminologies with bibliometric analysis, we find that though literature on “political instability” and “political risk” appeared earlier and have larger volume, research on “political uncertainty” is currently more active and catching up fast. Keywords with on-going citation bursts, two thirds of active co-citation clusters, and potentially transformative papers published recently are all related to political/policy uncertainty. The three strands of literature have obvious overlap and meanwhile their own special foci. Main areas of research on political instability, political uncertainty and political risk

Actor-Level Dynamicity: Its Distribution Analysis Eases Anomaly Detection in Longitudinal Networks

Different distributions have been observed across a wide variety of physical, biological, and man-made phenomena. For example, human height and blood pressure follow a normal distribution. Milk production by cows and the amount of rainfall follow a log-normal distribution. On the other side, the frequencies of words in most languages and family names best fit with the power-law distribution. Many real-life complex networks, such as author collaboration networks, also follow a power-law distribution. By considering four statistical distributions (i.e., normal, log-normal, exponential, and power-law), this paper first investigates the distribution of actor-level positional dynamicity in longitudinal networks. Positional dynamicity indicates the level of changes in actors' structural positions over time in a longitudinal network and has been used as a proxy for the actor-level dynamicity. The empirical investigation of two Facebook networks showed that actors' positional dynamicity values in longitudinal networks followed a power-law distribution. This power-law distribution did not change when different window sizes were used to explore the underlying longitudinal networks. This paper then explores how the power-law distribution of actor-level dynamicity values can be used for anomaly detection in longitudinal networks. The anomaly detection approach based on the power-law distribution of actors' positional dynamicity values revealed a superior application compared with a well-established anomaly detection approach. Finally, we discuss the implication of the power-law distribution of actor-level dynamicity in the context of other existing research problems related to complex networks.

Optimising cattle grazing distribution on rangeland: a systematic review and network analysis

Optimising beef cattle (Bos taurus and Bos indicus) distribution, both spatially and temporally, is one of the most significant challenges associated with managing extensive grazed rangelands. Landscape variability and behavioural patterns of cattle may lead to non-uniform and inefficient forage utilisation, damage to critical habitats, and water quality impairment. In order to overcome these distribution challenges, a large suite of tools have been developed and researched to optimise grazing patterns. The objectives of this synthesis paper are 2-fold: (i) to survey and categorise distribution tools; and (ii) to analyse the connectivity of existing research across academic disciplines to identify and isolate knowledge gaps. A systematic literature review revealed specific types of tools and strategies to improve cattle distribution, which were categorised as either ‘animal’ or ‘environmental manipulations’. Animal manipulations utilise aspects of individual behaviour and herd dynamics to alter grazing patterns, whereas environmental manipulations involve transforming aspects of the animal’s surroundings to overcome challenges associated with inefficient distribution. This review reveals that strategies are overwhelmingly studied in isolation, and that there is potential to increase efficacy by integrating multiple strategies to achieve a desired outcome. Motivated by these findings, an author collaboration network analysis was conducted to investigate connectivity within and among author fields of expertise to understand why more integrated management strategies are not currently studied. Authors were classified into five fields of research: animal behaviour science, animal production science, biophysical rangeland science, economics, and other. The network analysis revealed that communities of authors contributing to papers on enhancing cattle distribution are disjointed. These results suggest that in order to fulfil knowledge gaps about the efficacy and cost of management strategies, there needs to be interdisciplinary engagement with particular attention to strategies that integrate animal and environmental manipulations to enhance cattle grazing distribution on extensively grazed landscapes.

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer's disease neuroimaging initiative.

BackgroundAlzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years.MethodsCitation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time.ResultsDuring the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period.ConclusionsBoth statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.

A study on the author collaboration network in big data*

In order to obtain a deeper understanding of the collaboration status in the big data field, we investigated the author collaboration groups and the core author collaboration groups as well as the collaboration trends in big data by combining bibliometric analysis and social network analysis. A total of 4130 papers from 13,759 authors during the period of 2011–2015 was collected. The main results indicate that 3483 of the papers are coauthored (i.e., 84.33% of all papers) from 12,016 coauthors (i.e., 87.33% of all authors), which represent a reputable level of collaboration. On the other hand, 91.83% of all the identified coauthors have published only one paper so far, reflecting a poor level of maturity of such authors. Through social network analysis, we observed that the author collaboration network is composed of small author collaboration groups and also that the authors are mainly from the computer science & technology field. As an important contribution of our study, we further analyzed the author collaboration network, culminating in the generalization of four subnet modes, which were defined by some papers: ‘dual-core’, ‘complete’, ‘bridge’ and ‘sustainable development’. It was found that the dual-core mode stands for the stage that researchers have just begun to study big data. Beginning of big data research, the complete mode tends to joint research, both the dual-core and complete modes are mostly engaged in the same project, and the bridge mode and the sustainable development mode represent, respectively, the popular and valued directions in the big data field. The results of this study can be useful for researchers interested in finding suitable partners in the big data field. By tracking the core authors and the key author collaboration groups, one can learn about the current developments in the big data field as well as predict the development prospects of such a field. Therefore, we expect with the results of our study summarized in this paper to contribute to a faster development of the big data field.

The impact of collaboration and knowledge networks on citations

Research papers not only involve author collaboration networks but also relate to knowledge networks. Previous research claims that a paper’s citations are related to the node attributes of its authors in collaboration networks. We further propose that a paper’s citations can also be affected by the node attributes of its knowledge elements in knowledge networks. In this study, we develop a new method to construct the knowledge network using article keywords. Further, we explore the antecedents of paper citations from both the collaboration and knowledge network perspectives. Using wind energy paper data (16,351 records) collected from WoS (Web of Science) and JCR (Journal Citation Reports) database, we construct two distinct networks and empirically examine the hypotheses of the relationships between node attributes of two networks and the paper’s citations, which fill the gap in prior studies and will inspire related studies. We have the following key findings: in the collaboration network, the structural holes of authors have positive but non-significant effects on the paper’s citations, while the authors’ centrality has inverted U effects on the paper’s citations; in the knowledge network, the structural holes of knowledge elements are positively related to the paper’s citations, and the knowledge elements centrality has an inverted U relationship with the paper’s citations.

The Habits of Highly Effective Researchers: An Empirical Study

Interest in the habits of influential individuals cuts across domains. As researchers, we are intrigued why few attain significant eminence in their fields, whereas many operate in obscurity. An empirical examination of this question has been made possible by the recent availability of large scale publication data. In this paper, we use information from the AMiner Paper Citation and Author Collaboration Networks to discern factors that relate to the impact of influential researchers across five domains in the computing discipline. We propose and apply a novel algorithm to identify influential vertices in co-authorship networks built from total corpora of 1,00,000+ papers and 72,000+ authors over a span of more than 50 years. The results from our study indicate that the impact of these influential researchers relate to a variety of factors. Surprisingly, we find evidence across the domains that higher impact is associated with lower levels of collaboration, and authority.

Link prediction in author collaboration network based on BP neural network

Recently, more and more authors have been encouraged for collaboration because it often produces good results. However, the author collaboration network contains experts in various research directions within various fields, and it is difficult for individual authors to decide which authors are best suited to their expertise. This paper uses the relationships among authors to predict new relationships that may arise, recommending each author with the collaborators they may be interested in. The data source comes from 4-year data in DBLP from 2001 to 2004. After data cleaning, the training set and test set are constructed and then used BP neural network to build model. At the same time, this article compares the performance with Logistic Regression, SVM and Random Forest. The experiment shows that the BP neural network can get better result, and it is feasible to predict links in the author collaboration network.

Visualization analysis of author collaborations in schizophrenia research.

BackgroundSchizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research.MethodsThis study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from Science Citation Index Expanded (SCI Expanded) via Web of Science. CiteSpace III, an information visualization and analysis software, was used to make a visual analysis.ResultsCollaborative author networks within the field of schizophrenia were determined using published documents. We found that external author collaboration networks were more scattered while potential author collaboration networks were more compact. Results from hierarchical clustering analysis showed that the main collaborative field was genetic research in schizophrenia.ConclusionBased on the results, authors belonging to different institutions and in different countries should be encouraged to collaborate in schizophrenia research. This will help researchers focus their studies on key issues, and allow each other to offer reasonable suggestions for making polices and providing scientific evidence to effectively diagnose, prevent, and cure schizophrenia.

Heterogeneous Networks and Their Applications: Scientometrics, Name Disambiguation, and Topic Modeling

We present heterogeneous networks as a way to unify lexical networks with relational data. We build a unified ACL Anthology network, tying together the citation, author collaboration, and term-cooccurence networks with affiliation and venue relations. This representation proves to be convenient and allows problems such as name disambiguation, topic modeling, and the measurement of scientific impact to be easily solved using only this network and off-the-shelf graph algorithms.

Production and scientific collaboration in police training (1987-2011)

Purpose – The purpose of this paper is to identify and analyze the production and global scientific collaboration of research in police training from 1987 until 2011. Design/methodology/approach – Selecting databases, design of search strategy, download of bibliographic records, treatment of the bibliographic information, bibliometric analysis, identification of research groups and collaborative networks of institutions and countries has been the used methodology. Findings – Of all 1,928 papers reviewed by experts, 155 articles were related directly with police training with an average of 2.59 signatures per work, with 66.45 percent of articles signed in coauthorship. It is noted that in recent years there has been an increase in signatures and works. Articles published are distributed in journals of heterogeneous character associated to police training such as criminology, psychology, psychiatry, health or education. A significant amount of research is captained from a university scope, sometimes in collaboration with police institutions. Collaboration between members of the same institution and between institutions in the same country are predominant. Originality/value – To characterize the scientific production of the journals, authors, institutions and countries in the area of police training, as well as to identify the collaboration networks of authors, institutions and countries within the area.

The ACL anthology network corpus

We introduce the ACL Anthology Network (AAN), a comprehensive manually curated networked database of citations, collaborations, and summaries in the field of Computational Linguistics. We also present a number of statistics about the network including the most cited authors, the most central collaborators, as well as network statistics about the paper citation, author citation, and author collaboration networks.