Day of the week submission effect for accepted papers in Physica A,PLOS ONE,Nature and Cell

The particular day of the week when an event occurs seems to have unexpected consequences. For example, the day of the week when a paper is submitted to a peer reviewed journal correlates with whether that paper is accepted. Using an econometric analysis (a mix of log–log and semi-log based on undated and panel structured data) we find that more papers are submitted to certain peer review journals on particular weekdays than others, with fewer papers being submitted on weekends. Seasonal effects, geographical information as well as potential changes over time are examined. This finding rests on a large (178,000) and reliable sample; the journals polled are broadly recognized (Nature, Cell, PLOS ONE and Physica A). Day of the week effect in the submission of accepted papers should be of interest to many researchers, editors and publishers, and perhaps also to managers and psychologists.     

An empirical analysis of the relationship between individual characteristics and research productivity

This paper provides an analysis of the relationship between research performance and individual characteristics (e.g., career path information) of researchers, based on information provided in the curriculum vitaes of 565 excellent researchers within the life sciences and medical sciences fields in Japan. I specifically analyzed the relationship between the experiences of practical physicians and research performance. As a result, I found that the experience as a practical physician had a statistically positive relationship with the number of research papers, but there was not a significant relationship with the number of citations. Moreover, the diversity of a researcher’s career related significantly to the number of citations and patents. An employment experience at a young age with a company or independent administrative agency had a significant and positive relationship with number of coauthors. However, a significant relationship between work experience in a foreign country and research performance was not observed.     

The funding factor: a cross-disciplinary examination of the association between research funding and citation impact

This paper intends to illuminate the relationship between science funding and citation impact in seven STEMM disciplines (science, technology, engineering, mathematics, and medicine). Using a regression model with Heckman bias correction, we find that funding has a positive, significant association with a paper’s citations in STEMM fields. Further analyses show that this association is magnified by the factors of multiple authorship and multiple institutions. For funded papers in STEM, multi-author and multi-institution papers tend to receive even more citations than single-authored and single-institution papers; however, funded papers in Medicine received less gain in citation impact when either factor is considered. Based on the finding that funding support has a stronger association with citation impact when it is treated as a binary variable than as a count variable, this paper recommends the allocation of funding to researchers without active funding support, instead of giving awards to those with multiple funding supports at hand.     

Study on the destination of research via knowledge flows

Today, governments tackle the science of science policy with quantitative analysis, especially in the USA. This trend promotes the use of objective data by decision-makers in the fields of innovation policy and technology management. These decision-makers seek more reliable research and development at an earlier stage to contribute to the national economy. Under this worldwide trend, there is a high demand for quantitative analysis accompanying complex IT skills from governmental officers and non-IT researchers. The purpose of this research is to extract the destinations of currently growing fields of science by means of tracking citations and to capture signs of state of the art studies. The analysis data are bibliographic data of academic papers retrieved from Web of Science. I provide results for 16 growing topics as of July 2016. I deepen the understanding of the “convolutional neural network” among a lot of topics, and found future application candidates. I provide a methodology to discover future seeds of research and development. Additionally, the analysis system used in this research automatically publishes its results, and always provides the results. This research will contribute to improving strategies around research and development.     

Mapping institutions and their weak ties in a specialty: A case study of cystic fibrosis body composition research

The paper demonstrates visualization technique that show the collaboration structure of institutions in the specialty and the researchers that function as weak ties among them. Institution names were extracted from the collection of papers and disambiguated using the Derwent Analytics (v1.2) software product. Institutions were clustered into collaboration groups based on their co-occurrence in papers. A crossmap of clustered institutions against research fronts, which were derived using bibliographic coupling analysis, shows the research fronts that specific institutions participate in, their collaborator institutions and the research fronts in which those collaborations occurred. A crossmap of institutions to author teams, derived from co-authorship analysis, reveals research teams in the specialty and their general institutional affiliation, and further identifies the researchers that function as weak ties and the institutions that they link. The case study reveals that the techniques introduced in this paper can be used to extract a large amount of useful information about institutions participating in a research specialty.     

Effects of large-scale research funding programs: a Japanese case study

This study investigates the effects of large-scale research funding from the Japanese government on the research outcomes of university researchers. To evaluate the effects, we use the difference-in-differences estimator and measure research outcomes in terms of number of papers and citation counts per paper. Our analysis shows that the funding program led to an increase in the number of papers in some fields and an increase in the citation counts in the other fields. A comparison of our estimation results with assessment data obtained from peer reviews showed important differences. Since the characteristics of research vary according to the field, bibliometrics analysis should be used along with the peer review method for a more accurate analysis of research impact.     

Exploring the management information systems discipline: a scientometric study of ICIS, PACIS and ASAC

This paper examines the rapid growth of China in the field of nanotechnology and the rise of collaboration between China and the US in this emerging domain. Chinese scientific papers in nanotechnology are analyzed to indicate overall trends, leading fields and the most prolific institutions. Patterns of China–US nanotechnology paper co-authorship are examined over the period 1990–2009, with an analysis of how these patterns have changed over time. The paper combines bibliometric analysis and science mapping. We find rapid development in the number of China–US co-authored nanotechnology papers as well as structural changes in array of collaborative nanotechnology sub-fields. Implications for both China and the US of this evolving relationship are discussed.     

Collaboration network patterns and research performance: the case of Korean public research institutions

This study examines the impact of collaborating patterns on the R&;D performance of public research institutions (PRIs) in Korea’s science and engineering fields. For the construction of R&;D collaborating networks based on the co-authorship data of 127 institutions in Scopus, this paper proposes four types of collaborations by categorizing network analyses into two dimensions: structural positions (density, efficiency, and betweeness centrality) and the relational characteristics of individual nodes (eigenvector and closeness centralities). To explore the research performance by collaboration type, we employ a data envelopment analysis window analysis of a panel of 23 PRIs over a 10-year period. Comparing the R&;D productivities of each group, we find that the PRIs of higher productivity adhere to a cohesive networking strategy, retaining intensive relations with their existing partners. The empirical results suggest that excessively cohesive alliances might end up in ‘lock-in’ relations, hindering the exploitation of new opportunities for innovation. These findings are implicit in relation to the Korean Government’s R&;D policies on collaborating strategies to produce sustained research results with the advent of the convergence research era.     

To be the Prince to wake up Sleeping Beauty: the rediscovery of the delayed recognition studies

In science, sleeping papers, previously known as “Sleeping Beauties”, refer to scientific papers that are recognized by the scientific community after a long hibernation period following their publication. Many factors may contribute to their delayed yet exceptional popularity, such as the introduction of new technologies or ideas that are beyond the capabilities at the time of publication. The recognition of a sleeping paper, often through a paper that cites the sleeping paper and has a profound impact on the research area, is important to the scientific community. Here, we proposed a method to identify the paper that rediscovers a sleeping paper, known as a rediscovering paper, based on the citation network of the sleeping paper. Based on the 15 rediscovering papers obtained from the top sleeping papers in science, we introduced 5 feature indices of the leading authors of these rediscovering papers (rediscovering authors) defined by an academic search system AMiner (https://cn.aminer.org/). The 5 feature indices depict academic achievements of researchers from various aspects: Publication, Citation, Longevity, H-index and Sociability. The rediscovering authors lead to most general scientific authors in the 5 feature indices. Our results reveal common features of potential rediscovering authors in the scientific community who may play significant roles in the propagation of citation networks.     

Funding acknowledgement analysis: an enhanced tool to investigate research sponsorship impacts: the case of nanotechnology

There is increasing interest in assessing how sponsored research funding influences the development and trajectory of science and technology. Traditionally, linkages between research funding and subsequent results are hard to track, often requiring access to separate funding or performance reports released by researchers or sponsors. Tracing research sponsorship and output linkages is even more challenging when researchers receive multiple funding awards and collaborate with a variety of differentially-sponsored research colleagues. This article presents a novel bibliometric approach to undertaking funding acknowledgement analysis which links research outputs with their funding sources. Using this approach in the context of nanotechnology research, the article probes the funding patterns of leading countries and agencies including patterns of cross-border research sponsorship. We identify more than 91,500 nanotechnology articles published worldwide during a 12-month period in 2008–2009. About 67% of these publications include funding acknowledgements information. We compare articles reporting funding with those that do not (for reasons that may include reliance on internal core-funding rather than external awards as well as omissions in reporting). While we find some country and field differences, we judge that the level of reporting of funding sources is sufficiently high to provide a basis for analysis. The funding acknowledgement data is used to compare nanotechnology funding policies and programs in selected countries and to examine their impacts on scientific output. We also examine the internationalization of research funding through the interplay of various funding sources at national and organizational levels. We find that while most nanotechnology funding is nationally-oriented, internationalization and knowledge exchange does occur as researchers collaborate across borders. Our method offers a new approach not only in identifying the funding sources of publications but also in feasibly undertaking large-scale analyses across scientific fields, institutions and countries.     

Sixty-four years of informetrics research: productivity,impact and collaboration

This paper analyses the information science research field of informetrics to identify publication strategies that have been important for its successful researchers. The study uses a micro-analysis of informetrics researchers from 5,417 informetrics papers published in 7 core informetrics journals during 1948–2012. The most productive informetrics researchers were analysed in terms of productivity, citation impact, and co-authorship. The 30 most productive informetrics researchers of all time span several generations and seem to be usually the primary authors of their research, highly collaborative, affiliated with one institution at a time, and often affiliated with a few core European centres. Their research usually has a high total citation impact but not the highest citation impact per paper. Perhaps surprisingly, the US does not seem to be good at producing highly productive researchers but is successful at producing high impact researchers. Although there are exceptions to all of the patterns found, researchers wishing to have the best chance of being part of the next generation of highly productive informetricians may wish to emulate some of these characteristics.     

Exploiting Structural Similarities to Classify Citations

Citations play an important role in the scientific community by assisting in measuring multifarious policies like the impact of journals, researchers, institutions, and countries. Authors cite papers for different reasons, such as extending previous work, comparing their study with the state-of-the-art, providing background of the field, etc. In recent years, researchers have tried to conceptualize all citations into two broad categories, important and incidental. Such a categorization is very important to enhance scientific output in multiple ways, for instance, (1) Helping a researcher in identifying meaningful citations from a list of 100 to 1000 citations (2) Enhancing the impact factor calculation mechanism by more strongly weighting important citations, and (3) Improving researcher, institutional, and university rankings by only considering important citations. All of these uses depend upon correctly identifying the important citations from the list of all citations in a paper. To date, researchers have utilized many features to classify citations into these broad categories: cue phrases, in-text citation counts, and metadata features, etc. However, contemporary approaches are based on identification of in-text citation counts, mapping sections onto the Introduction, Methods, Results, and Discussion (IMRAD) structure, identifying cue phrases, etc. Identifying such features accurately is a challenging task and is normally conducted manually, with the accuracy of citation classification demonstrated in terms of these manually extracted features. This research proposes to examine the content of the cited and citing pair to identify important citing papers for each cited paper. This content similarity approach was adopted from research paper recommendation approaches. Furthermore, a novel section-based content similarity approach is also proposed. The results show that solely using the abstract of the cited and citing papers can achieve similar accuracy as the state-of-the-art approaches. This makes the proposed approach a viable technique that does not depend on manual identification of complex features.     

Neo-colonialism and research collaboration in Central Africa

The study examines aspects of both neo-colonial ties and neo-colonial science in research papers produced by Central African countries. The primary focus is on the extent and pattern of neo-colonial ties and other foreign participation in the co-authorship of Central African research papers. The analysis revealed that 80% of Central Africa’s research papers are produced in collaboration with a partner from outside the region. Moreover, 46% of papers are produced in collaboration with European countries as the only partner, and 35% in collaboration with past colonial rulers. The top collaborating countries are France (32%), the USA (14%), and the UK and Germany (both 12%). Foreign powers also facilitate the production of regionally and continentally co-authored papers in Central Africa, where European countries participate in 77% of regionally co-authored papers. The practice of neo-colonial science, on the other hand, features in a survey of reprint authors of Cameroonian papers. The survey investigated specific contributions made by Cameroon coauthors to the research processes underlying a paper. Cameroonian researchers contribute intellectually and conceptually to the production of research papers, irrespective of whether the collaboration involves partners from past colonial or non-colonial countries. Their most frequent role in collaborative research with foreign researchers remains the conduct of fieldwork.     

Mapping the Intellectual Structure of Research on ‘Born Global’ Firms and INVs: A Citation/Co-citation Analysis

The present research paper shows the results of an analysis of the existing literature on one of the topics that has sparked the most interest among scholars and researchers in the fields of international management and entrepreneurship: born global firms or international new ventures. Concretely, with the aim of identifying and visualising the intellectual structure of research on this phenomenon, a total of 124 research papers whose titles contain the above terms are analysed. The methodology is mainly based on the bibliometric techniques of document citation and co-citation analyses and the analysis of social networks.     

Transfer and distribution of knowledge creation activities of bio-scientists in knowledge space

In order to explore the rule of knowledge creation activities at both temporal and spatial scales, this paper makes statistical analysis of the time interval and spatial displacement of consecutive knowledge creation activities of high-yield, low-yield, and ASFP (all the scientists published at least four papers), respectively. The research shows that, for high-yield scientists, the time interval of knowledge creation activities obeys heavy-tailed distribution and embodies bursting features, with both long-time silence and intensive burst of creation activities. The time interval distribution of low-yield scientists is approximate to exponential distribution, and is often randomly and occasionally distributed. For ASFP, the spatial distribution of creation activities also embodies heavy-tailed features, where their activities are intensively confined to a certain knowledge field, and where long-distance exploration across the knowledge fields has also been made in knowledge creation activities.     

To include or not: the role of review papers in citation-based analysis

Citation information helps researchers observe the evolution of the knowledge. In scientific publications, a review paper discusses a professional field and thus tends to have more citations than general papers do. This study investigated whether specific characteristics of review papers induce different results in citation-based analysis. From the Scopus database, we collected scientific publications in a specific research field, e-tourism, to examine the role of review papers in citation-based analysis. The dataset includes 1421 publications covering the period from the 1988–2015. Empirical statistics show that review papers’ specific citation patterns influence citation analysis. First, in the main path analysis, the result expresses review papers’ integrative role in linking papers from diverse perspectives toward a clear mainstream topic. Second, in a well-defined research context, review papers introduce bias in citation-based clustering analysis because the specific high citation pattern in review papers obfuscates the grouping process. When using citation information in analysis, scholars must consider the purpose of the study and treat review papers distinctly to avoid bias when using certain analysis methods and datasets.     

Bibliometric analysis of the Czech research publications from 1994 to 2005

We have compared bibliometric data of Czech research papers generated from 1994 to 2005 with papers from six other EU countries: Austria, Hungary, Poland, Finland, Ireland and Greece. The Czech Republic ranked the fifth in number of papers per thousand inhabitants and the sixth in number of citations/paper. Relatively the most cited were Czech papers from fields Engineering and Mathematics ranking the third, and Computer Science, Environment/Ecology and Molecular Biology ranking the fourth among 7 EU countries. Our analysis indicates that Czech research is lagging behind the leading EU countries, but its output is proportional to the R&D expenses.     

LitStoryTeller+: an interactive system for multi-level scientific paper visual storytelling with a supportive text mining toolbox

The continuing growth of scientific publications has posed a double-challenge to researchers, to not only grasp the overall research trends in a scientific domain, but also get down to research details embedded in a collection of core papers. Existing work on science mapping provides multiple tools to visualize research trends in domain on macro-level, and work from the digital humanities have proposed text visualization of documents, topics, sentences, and words on micro-level. However, existing micro-level text visualizations are not tailored for scientific paper corpus, and cannot support meso-level scientific reading, which aligns a set of core papers based on their research progress, before drilling down to individual papers. To bridge this gap, the present paper proposes LitStoryTeller+, an interactive system under a unified framework that can support both meso-level and micro-level scientific paper visual storytelling. More specifically, we use entities (concepts and terminologies) as basic visual elements, and visualize entity storylines across papers and within a paper borrowing metaphors from screen play. To identify entities and entity communities, named entity recognition and community detection are performed. We also employ a variety of text mining methods such as extractive text summarization and comparative sentence classification to provide rich textual information supplementary to our visualizations. We also propose a top-down story-reading strategy that best takes advantage of our system. Two comprehensive hypothetical walkthroughs to explore documents from the computer science domain and history domain with our system demonstrate the effectiveness of our story-reading strategy and the usefulness of LitStoryTeller+.

     

International contact and research performance

The scope of this article is to illuminate the relationship between degree of international contact and research performance among researchers in small countries. Comparisons are done between the natural, medical and social sciences, technology and the humanities. Three indicators on international contact are used: a) an index on contact frequency, b) type of conference attendance, and c) long-term research stays abroad. There is a relatively strong correlation between contact frequency and international publishing activity in all fields of learning. Researchers who were invited to present a paper by conference organizers were considerably more productive than those who gave a paper on their own initiative, and this latter group was in turn much more productive than those researchers who attended without papers. Contrary to other forms of contact, long-term research stays abroad have a very small independent effect on international publishing.     

All author citations versus first author citations

Based on a set of information science papers this study demonstrates that "all author" citationcounts should be preferred when visualizing the structure of research fields. "First author" citationstudies distort the picture in terms of most influential researchers, while the subfield structuretends to be just about the same for both methods.