Scopes of accounting journals and published papers: what do they signalize?

Our main objective is to create a framework to analyze signals sent from academic journals. The signals chosen for the framework were: journal’ scopes; and the latest published papers. We apply the framework to the field of accounting with the main focus of categorizing the journal scopes and the latest published articles into research topics by using text mining techniques. We analyze the published papers of research topics in accounting journals during the 2016–2018 period. Another objective is to compare research topics from the last published papers with research topics identified in accounting journal scopes. We found a majority of journals with a broader scope in terms of accounting research areas, but we see a concentration on specific research topics by analyzing the papers. In addition, the most signaled accounting areas in scopes are financial accounting and auditing. The framework helps us categorize 5270 research papers into accounting research topics correctly, faster than manually reading titles, abstracts, and keywords. While specific scopes may carry the risk of missing new research trends, broad scopes may require more reviewers from different research areas. Diversity can be seen as applying other methodological choices, theoretical lenses, and conceptual or empirical research approaches. We believe that academic diversity is for the benefit of accounting research.

     

Topic-based Pagerank: toward a topic-level scientific evaluation

Within the same research field, different subfields and topics may exhibit varied citation behaviors and scholarly communication patterns. For a more effect scientific evaluation at the topic level, this study proposes a topic-based PageRank approach. This approach aims to evaluate the scientific impact of research entities (e.g., papers, authors, journals, and institutions) at the topic-level. The proposed topic-based PageRank, when applied to a data set on library and information science publications, has effectively detected a variety of research topics and identified authors, papers, and journals of the highest impact from each topic. Evaluation results show that compared with the standard PageRank and a topic modeling technique, the proposed topic-based PageRank has the best performance on relevance and impact. Different perspectives of organizing scientific literature are also discussed and this study recommends the mode of organization that integrates stable research domains and dynamic topics.     

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+.

     

Researcher dynamics in the generation of emerging topics in life sciences and medicine

Understanding the driving forces that generate emerging topics (ETs or Emerging Research Topics) will assist in the sound development of science and technologies. In the present study, we aim to clarify the researcher dynamics of generating and developing ETs in life sciences and medicine over the past half-century by analyzing the pre-, contemporary-, and post-participation of researchers publishing articles containing the emerging keywords that are elements of ETs. Our results suggest that, while manpower needs for publication have increased, less manpower is actually required to generate ETs these days and that pre-participation in certain research topics has become important to generate regular ETs but not Nobel Prize-class ones. Finally, we discovered that, in this post-genomic era, those researchers who generate ETs also continue to focus on those fields. These trends illustrate a mode shift in the scientific practice of researchers that have generated and developed ETs over the last 50 years as well as highlight the significance of funding projects with high probabilities of generating high-impact ETs.

     

Comparing the scientific quality achieved by funding instruments for single grant holders and for collaborative networks within a research system: Some observations

Increasingly, funding of academic research is carried out through the support of collaboration, rather than through single awards to a sole grant holder. The practice is well supported by evidence that larger, network-based research achieves high quality while leading to a number of capacity building benefits for the research system, although with significant transaction costs. However, the question of what kind of funding schemes should be made available to researchers is not a simple dichotomy between single grant-holder projects and networks. A key question is how to achieve a balance in each subject field between different forms of funding instrument employed while ensuring different forms of funding retain a reputation for generating research of high scientific quality. This paper reports the results of a systematic comparison of the scientific quality of 1010 scientific papers from the ISI database produced under two contrasting forms of funding instrument for a single year in the Austrian science system. Comparison of the arcsinh transformed citation counts of papers from the two main forms of funding for basic science at the level of main scientific field shows there is no statistically significant difference in the quality achieved by the two forms of funding. This may suggest that funders and research performers have succeeded in ensuring that different research instruments nevertheless achieve very similar levels of scientific excellence.     

Computer science research: more production,less productivity

It is commonly accepted that scientific research or, more precisely, the number of scientific publications, in computer science has greatly increased over the last few years. The reason would appear to be the pressure to publish, coined by the expression ”Publish or perish”, which is, among other things, necessary for promotions and applications for grants or projects. In this paper we have conducted a study that covers computer science publications from 1936 to 2010 in order to quantify this increase in publications regarding computing research. We have considered the computing conferences and journals available in the DBLP computer science bibliography (DBLP 2013) database, including more than 1.5 million papers, and more than 4 million authors (more than 900,000 different people), corresponding to about 1,000 different journals and 3,000 different conferences and workshops. Our study confirms and quantifies these increases with regard to the number of papers, number of authors, number of papers per author, etc. However, it also reaches a surprising conclusion: the real productivity of researchers has decreased throughout history. The reason for this decrease is the average number of authors per paper, which has grown significantly and is currently three.     

SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

The growing collection of scientific data in various web repositories is referred to as Scientific Big Data, as it fulfills the four “V’s” of Big Data–-volume, variety, velocity, and veracity. This phenomenon has created new opportunities for startups; for instance, the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs. Traditionally, the content of the papers are compared to list the relevant papers from a repository. The conventional method results in a long list of papers that is often impossible to interpret productively. Therefore, the need for a novel approach that intelligently utilizes the available data is imminent. Moreover, the primary element of the scientific knowledge base is a research article, which consists of various logical sections such as the Abstract, Introduction, Related Work, Methodology, Results, and Conclusion. Thus, this study utilizes these logical sections of research articles, because they hold significant potential in finding relevant papers. In this study, comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results (i.e., retrieving relevant papers). Therefore, we proposed, implemented, and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing terms. The section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer science. Overall, the proposed approach extracted 14% more relevant results from the entire dataset. As the experimental results suggested that employing a finer content similarity technique improved the quality of results, the proposed approach has led the foundation of knowledge-based startups.     

Medical research in South Africa: a scientometric analysis of trends,patterns, productivity and partnership

Being a scientifically active country in Africa, South Africa has made significant strides in the production of scientific publications. Medicine is one branch of science that has achieved a remarkable position in this regard. Extracting and analyzing medical publications for three decades and at regular intervals (1975–2005) from the SCI database, this paper pioneers an attempt to find out whether the reported pace of growth in the production of scientific papers in medicine is an effect of partnerships that scholars have with their counterparts within the organization, within the country, or with those in other countries. This paper also presents the unique patterns of scientific research in medicine, taking into account factors such as the count and fractional count of papers, citations, trends of growth, sectoral participation, partners, and publication outlets, and seeks to provide new insights into the directions medical science is taking in South Africa today.     

Patent research in the field of library and information science: Less useful or difficult to explore?

Patents and relevant topics are gaining momentum in economic analysis and scientific research with the rapid global intellectual property filings growth. However, a corresponding increase seems to be unspectacular in patent research publications, especially under the category of information science and library science. This paper provided a retrospect to the existing studies on patents collected from web of science and emphatically characterized the current situation through performing a series of bibliometric analysis. Prominent authors and institutions from mainland China, Taiwan and Belgium have carried out various studies on patent separately or jointly. Topics involved in 884 journal papers are reclassified from perspectives of the development, application and analysis of patents based on the results of keyword co-occurrence and typical publications in each stage. The final, but the novel part of this study was a sentence-by-sentence analysis of conclusive and citing ideas of recent publications, for tracing problems and potential researchable topics and indicating that patent research still has more spaces to move up.     

Sleeping beauties cited in patents: Is there also a dormitory of inventions?

A ‘Sleeping Beauty in Science’ is a publication that goes unnoticed (‘sleeps’) for a long time and then, almost suddenly, attracts a lot of attention (‘is awakened by a prince’). In our foregoing study we found that roughly half of the Sleeping Beauties are application-oriented and thus are potential Sleeping Innovations. In this paper we investigate a new topic: Sleeping Beauties that are cited in patents. In this way we explore the existence of a dormitory of inventions. To our knowledge this is the first study of this kind. We investigate the time lag between publication of the Sleeping Beauty and the first citation by a patent. We find that patent citation may occur before or after the awakening and that the depth of the sleep, i.e., citation rate during the sleeping period, is no predictor for later scientific or technological impact of the Sleeping Beauty. A surprising finding is that Sleeping Beauties are significantly more cited in patents than ‘normal’ papers. Inventor–author self-citations relations occur only in a small minority of the Sleeping Beauties that are cited in patents, but other types of inventor–author links occur more frequently. We develop an approach in different steps to explore the cognitive environment of Sleeping Beauties cited in patents. First, we analyze whether they deal with new topics by measuring the time-dependent evolution in the entire scientific literature of the number of papers related to both the precisely defined topics as well as the broader research theme of the Sleeping Beauty during and after the sleeping time. Second, we focus on the awakening by analyzing the first group of papers that cites the Sleeping Beauty. Third, we create concept maps of the topic-related and the citing papers for a time period immediately following the awakening and for the most recent period. Finally, we make an extensive assessment of the cited and citing relations of the Sleeping Beauty. We find that tunable co-citation analysis is a powerful tool to discover the prince(s) and other important application-oriented work directly related to the Sleeping Beauty, for instance papers written by authors who cite Sleeping Beauties in both the patents of which they are the inventors, as well as in their scientific papers.     

Research profiling for ‘standardization and innovation’

This paper addresses the profiling of research papers on ‘standardization and innovation’—exploring major topics and arguments in this field. Drawing on 528 papers retrieved from the database, Web of Science, we employed trend, factor, and clustering analyses to demonstrate that the standardization and innovation research has continuously grown from publication of 13 papers in 1995 to 68 papers in 2008; the majority of these papers have been published in the six subject group domains of management, economics, environment, chemistry, computer science, and telecommunications. Technology innovation management specialty journals are the most central sources favorable for these themes. We also present an exploratory taxonomy that offers nine topical clusters to demonstrate the contextual structures of standardization and innovation. The implications of our results for ongoing consistent policy and future research into standardization and innovation are discussed.     

Benchmarking international scientific excellence: Are highly cited research papers an appropriate frame of reference?

This paper introduces a citation-based "systems approach" for analyzing the various institutional and cognitive dimensions of scientific excellence within national research systems. The methodology, covering several aggregate levels, focuses on the most highly cited research papers in the international journal literature. The distribution of these papers across institutions and disciplines enables objective comparisons their (possible) international-level scientific excellence. By way of example, we present key results from a recent series of analyses of the research system in the Netherlands in the mid 1990s, focussing on the performance of the universities across the various major scientific disciplines within the context of the entire system"s scientific performance. Special attention is paid to the contribution in the world"s top 1% and top 10% most highly cited research papers. The findings indicate that these high performance papers provide a useful analytical framework - both in terms of transparency, cognitive and institutional differentiation, as well as its scope for domestic and international comparisons - providing new indicators for identifying "world class" scientific excellence at the aggregate level. The average citation scores of these academic "Centres of Scientific Excellence" appear to be an inadequate predictor of their production of highly cited papers. However, further critical reflection and in-depth validation studies are needed to establish the true potential of this approach for science policy analyses and evaluation of research performance. This revised version was published online in August 2006 with corrections to the Cover Date.     

基于知识图谱的国内设计史研究现状与进展

随着国内设计产业、设计学的迅速发展,设计史在设计学研究领域的地位和价值进一步凸显,成为设计学研究领域的重要单元,以文献计量方法和知识图谱的形式分析和研究国内设计史现状与进展。以中国知网数据库收录的441条核心期刊论文数据为样本,应用CiteSpace文献计量数据分析软件,构建和分析国内设计史研究知识图谱,从文献数据的总体发文趋势、主题、引频、     

Mapping the social and behavioral sciences world-wide: Use of maps in portfolio analysis of national research efforts

We have developed a method to identify and map the internationally most visible research topics occurring in the social and behavioral sciences, as well as the topics which changed most over a decade. Methods and data relevent to a portfolio analysis of national research efforts are described. Keywords used by authors in scientific or scholarly publications provide a window on scientific developments and changes in scientific research. Using an interdisciplinary database, the SSCI, developments in publications were traced world-wide and for the US, UK, France, Germany, and the Netherlands. We compared two periods: 1981–85 and 1986–90 We discuss the major substantive developments occurring during 1981–1990, as visible in maps depicting both topics and disciplines. It is shown that the maps, enriched with scientometric indicators of strengths and weaknesses of national research efforts, can be important tools for science policy. The findings indicate that the research front on many topics in both social and behavioral sciences is international in the late 1980s.     

The growing number of patent citations to scientific papers: Changes in the world,nations, and fields

This study analyzes USPTO patents in the period 1998–2017. The number of science-related patents has increased twice as fast as the number of patents and scientific publications, and the number of cited papers per patent has almost doubled. These results vary substantially from one scientific and technological field to another. The proportion of the research papers cited by a patent has doubled. It refers to papers that are mostly published by the countries that have developed both scientific and technological capability and, surprisingly, are mainly used by inventors abroad. However, a weak relationship between the number of citations received from patents and papers reveals that the assessment of research performance needs some changes as the percentage of papers related to the innovations has grown over time.     

The citation advantage of foreign language references for Chinese social science papers

Contemporary scientific exchanges are international, yet language continues to be a persistent barrier to scientific communication, particularly for non-native English-speaking scholars. Since the ability to absorb knowledge has a strong impact on how researchers create new scientific knowledge, comprehensive access to and understanding of both domestic and international scientific publications is essential for scientific performance. This study explores the effect of absorbed knowledge on research impact by analyzing the relationship between the language diversity of cited references and the number of citations received by the citing paper. Chinese social sciences are taken as the research object, and the data, 950,302 papers published between 1998 and 2013 with 8,151,327 cited references, were collected from the Chinese Social Sciences Citation Index. Results show that there is a stark increase in the consumption of foreign language material within the Chinese social science community, and English material accounts for the vast majority of this consumption. Papers with foreign language references receive significantly more citations than those without, and the citation advantage of these internationalized work holds when we control for characteristics of the citing papers, such as the discipline, prestige of journal, prestige of institution, and scientific collaboration. However, the citation advantage has decreased from 1998 to 2008, largely as an artifact of the increased number of papers citing foreign language material. After 2008, however, the decline of the citation advantage subsided and became relatively stable, which suggests that incorporating foreign language literature continues to increase scientific impact, even as the scientific community itself becomes increasingly international. However, internationalization is not without concerns: the work closes with a discussion of the potential problems associated with the lack of linguistic diversity in scientific communication.

     

An analysis of global research funding from subject field and funding agencies perspectives in the G9 countries

This study analyzed journal articles published by authors from the G9 countries (Canada, China, France, Germany, Italy, Japan, Russia, the United Kingdom, and the United States) to identify the distribution of research funding and funding agencies in these countries. A total of 5,856,744 articles published between 2009 and 2014 were collected from the Web of Science database. The results showed that China had the highest proportion of funded papers among its overall scientific output, while Italy had the lowest funded paper ratio. The leading sponsoring countries of papers by other countries were China and the United States, with China having a sponsorship surplus with all the other G9 countries, and the United States having a sponsorship surplus with seven other countries excepting China. Furthermore, governmental agencies were the major sponsors of funded papers in the G9 countries. The field of life sciences had the highest proportion of funded papers among the field’s total paper output; while natural sciences had the highest proportion of papers among all funded papers of a country. Regarding funding agencies, the top three funding agencies in each G9 country were primarily domestic agencies; and a large proportion of the funding provided by these agencies were granted to domestic research projects.     

Discovering cross-topic collaborations among researchers by exploiting weighted association rules

Identifying the most relevant scientific publications on a given topic is a well-known research problem. The Author-Topic Model (ATM) is a generative model that represents the relationships between research topics and publication authors. It allows us to identify the most influential authors on a particular topic. However, since most research works are co-authored by many researchers the information provided by ATM can be complemented by the study of the most fruitful collaborations among multiple authors. This paper addresses the discovery of research collaborations among multiple authors on single or multiple topics. Specifically, it exploits an exploratory data mining technique, i.e., weighted association rule mining, to analyze publication data and to discover correlations between ATM topics and combinations of authors. The mined rules characterize groups of researchers with fairly high scientific productivity by indicating (1) the research topics covered by their most cited publications and the relevance of their scientific production separately for each topic, (2) the nature of the collaboration (topic-specific or cross-topic), (3) the name of the external authors who have (occasionally) collaborated with the group either on a specific topic or on multiple topics, and (4) the underlying correlations between the addressed topics. The applicability of the proposed approach was validated on real data acquired from the Online Mendelian Inheritance in Man catalog of genetic disorders and from the PubMed digital library. The results confirm the effectiveness of the proposed strategy.