- Journal Details
- First Published
- 30 Mar 2017
- Publication timeframe
- 4 times per year
- Open Access
Page range: 1 - 4
- Open Access
A Discrimination Index Based on Jain's Fairness Index to Differentiate Researchers with Identical H-index Values
Page range: 5 - 18
This paper proposes a discrimination index method based on the Jain's fairness index to distinguish researchers with the same H-index.
A validity test is used to measure the correlation of D-offset with the parameters, i.e. H-index, the number of cited papers, the total number of citations, the number of indexed papers, and the number of uncited papers. The correlation test is based on the Saphiro-Wilk method and Pearson's product-moment correlation.
The result from the discrimination index calculation is a two-digit decimal value called the discrimination-offset (D-offset), with a range of D-offset from 0.00 to 0.99. The result of the correlation value between the D-offset and the number of uncited papers is 0.35, D-offset with the number of indexed papers is 0.24, and the number of cited papers is 0.27. The test provides the result that it is very unlikely that there exists no relationship between the parameters.
For this reason, D-offset is proposed as an additional parameter for H-index to differentiate researchers with the same H-index. The H-index for researchers can be written with the format of “H-index: D-offset”.
D-offset is worthy to be considered as a complement value to add the H-index value. If the D-offset is added in the H-index value, the H-index will have more discrimination power to differentiate the rank of the researchers who have the same H-index.
- Discrimination index
- Jain's fairness index
- Open Access
Page range: 19 - 34
Research dynamics have long been a research interest. It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject. A micro perspective of research dynamics, however, concerning a single researcher or a highly cited paper in terms of their citations and “citations of citations” (forward chaining) remains unexplored.
In this paper, we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance, and topic innovation in each generation of forward chaining.
For highly cited work, scientific influence exists in indirect citations. Topic modeling can reveal how long this influence exists in forward chaining, as well as its influence.
This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations. Paraphrasing or semantically similar concept may be neglected in this research.
This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining. This can serve as an inspiration on how to adequately evaluate research influence.
The main contributions of this paper are the following three aspects. First, besides research dynamics of topic inheritance and topic innovation, we model topic disappearance by using a cross-collection topic model. Second, we explore the length and character of the research impact through “citations of citations” content analysis. Finally, we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton's publications and the topic dynamics of forward chaining.
- Research dynamics
- Forward chaining
- Topic model
- Scientific influence
- Citations content analysis
- Open Access
Page range: 35 - 42
We study the proportion of Web of Science (WoS) citation links that are represented in the Crossref Open Citation Index (COCI), with the possible aim of using COCI in research evaluation instead of the WoS, if the level of coverage was sufficient.
We calculate the proportion on citation links where both publications have a WoS accession number and a DOI simultaneously, and where the cited publications have had at least one author from our institution, the Czech Technical University in Prague. We attempt to look up each such citation link in COCI.
We find that 53.7% of WoS citation links are present in the COCI. The proportion varies largely by discipline. The total figures differ significantly from 40% in the large-scale study by Van Eck, Waltman, Larivière, and Sugimoto (blog 2018,
The sample does not cover all science areas uniformly; it is heavily focused on Engineering and Technology, and only some disciplines of Natural Sciences are present. However, this reflects the real scientific orientation and publication profile of our institution.
The current level of coverage is not sufficient for the WoS to be replaced by COCI for research evaluation.
The present study illustrates a COCI vs WoS comparison on the scale of a larger technical university in Central Europe.
- Open citations
- Crossref Open Citation Index
- Web of Science
- Current Research Information System
- Open Access
Page range: 43 - 55
The main objective of this work is to show the potentialities of recently developed approaches for automatic knowledge extraction directly from the universities’ websites. The information automatically extracted can be potentially updated with a frequency higher than once per year, and be safe from manipulations or misinterpretations. Moreover, this approach allows us flexibility in collecting indicators about the efficiency of universities’ websites and their effectiveness in disseminating key contents. These new indicators can complement traditional indicators of scientific research (e.g. number of articles and number of citations) and teaching (e.g. number of students and graduates) by introducing further dimensions to allow new insights for “profiling” the analyzed universities.
Webometrics relies on web mining methods and techniques to perform quantitative analyses of the web. This study implements an advanced application of the webometric approach, exploiting all the three categories of web mining: web content mining; web structure mining; web usage mining. The information to compute our indicators has been extracted from the universities’ websites by using web scraping and text mining techniques. The scraped information has been stored in a NoSQL DB according to a semi-structured form to allow for retrieving information efficiently by text mining techniques. This provides increased flexibility in the design of new indicators, opening the door to new types of analyses. Some data have also been collected by means of batch interrogations of search engines (Bing,
The main findings of this study concern the evaluation of the potential in digitalization of universities, in particular by presenting techniques for the automatic extraction of information from the web to build indicators of quality and impact of universities’ websites. These indicators can complement traditional indicators and can be used to identify groups of universities with common features using clustering techniques working with the above indicators.
The results reported in this study refers to Italian universities only, but the approach could be extended to other university systems abroad.
The approach proposed in this study and its illustration on Italian universities show the usefulness of recently introduced automatic data extraction and web scraping approaches and its practical relevance for characterizing and profiling the activities of universities on the basis of their websites. The approach could be applied to other university systems.
This work applies for the first time to university websites some recently introduced techniques for automatic knowledge extraction based on web scraping, optical character recognition and nontrivial text mining operations (
- Development of data and information services
- Webometrics indicators
- Higher education institutions
- Automatic extraction
- Machine learning
- Open Access
Page range: 56 - 74
In studies of the research process, the association between how researchers conceptualize research and their strategic research agendas has been largely overlooked. This study aims to address this gap.
This study analyzes this relationship using a dataset of more than 8,500 researchers across all scientific fields and the globe. It studies the associations between the dimensions of two inventories: the Conceptions of Research Inventory (CoRI) and the Multi-Dimensional Research Agenda Inventory—Revised (MDRAI-R).
The findings show a relatively strong association between researchers’ conceptions of research and their research agendas. While all conceptions of research are positively related to scientific ambition, the findings are mixed regarding how the dimensions of the two inventories relate to one another, which is significant for those seeking to understand the knowledge production process better.
The study relies on self-reported data, which always carries a risk of response bias.
The findings provide a greater understanding of the inner workings of knowledge processes and indicate that the two inventories, whether used individually or in combination, may provide complementary analytical perspectives to research performance indicators. They may thus offer important insights for managers of research environments regarding how to assess the research culture, beliefs, and conceptualizations of individual researchers and research teams when designing strategies to promote specific institutional research focuses and strategies.
To the best of the authors’ knowledge, this is the first study to associate research agendas and conceptions of research. It is based on a large sample of researchers working worldwide and in all fields of knowledge, which ensures that the findings have a reasonable degree of generalizability to the global population of researchers.
- Conception of research
- Research agendas
- Researchers’ beliefs
- Research strategy
- Views of research
- Research processes
- Open Access
Current Status and Enhancement of Collaborative Research in the World: A Case Study of Osaka University
Page range: 75 - 85
The purpose of this research is to provide evidence for decision-makers to realize the potentials of collaborations between countries/regions via the scientometric analysis of co-authoring in academic publications.
The approach is that Osaka University, which has set a strategy to become a global campus, is positioned to have a leading role to enhance such collaborations. This research measures co-authoring relations between Osaka University and other countries/regions to identify networks for fostering strong research collaborations.
Five countries are identified as candidates for the future global campuses of Osaka University based on three factors, co-authoring relations, GDP growth, and population growth.
The main limitation of this study is not being able to use the relations by the former positions of authors in Osaka University, because the data retrieved is limited by the query of the organization name at the first step.
The significance of this work is to provide evidence for the university strategy to expand abroad based on the quantity and visualization of trends.
With wider practical implementations, the approach of this research is useful in making a strategic roadmap for scientific organizations that intend to collaborate internationally.
- University management
- Overseas strategy
- Global campus
- Evidence-based policy-making
- Open Access
Global Collaboration in Artificial Intelligence: Bibliometrics and Network Analysis from 1985 to 2019
Page range: 86 - 115
This study aims to explore the trend and status of international collaboration in the field of artificial intelligence (AI) and to understand the hot topics, core groups, and major collaboration patterns in global AI research.
We selected 38,224 papers in the field of AI from 1985 to 2019 in the core collection database of Web of Science (WoS) and studied international collaboration from the perspectives of authors, institutions, and countries through bibliometric analysis and social network analysis.
The bibliometric results show that in the field of AI, the number of published papers is increasing every year, and 84.8% of them are cooperative papers. Collaboration with more than three authors, collaboration between two countries and collaboration within institutions are the three main levels of collaboration patterns. Through social network analysis, this study found that the US, the UK, France, and Spain led global collaboration research in the field of AI at the country level, while Vietnam, Saudi Arabia, and United Arab Emirates had a high degree of international participation. Collaboration at the institution level reflects obvious regional and economic characteristics. There are the Developing Countries Institution Collaboration Group led by Iran, China, and Vietnam, as well as the Developed Countries Institution Collaboration Group led by the US, Canada, the UK. Also, the Chinese Academy of Sciences (China) plays an important, pivotal role in connecting the these institutional collaboration groups.
First, participant contributions in international collaboration may have varied, but in our research they are viewed equally when building collaboration networks. Second, although the edge weight in the collaboration network is considered, it is only used to help reduce the network and does not reflect the strength of collaboration.
The findings fill the current shortage of research on international collaboration in AI. They will help inform scientists and policy makers about the future of AI research.
This work is the longest to date regarding international collaboration in the field of AI. This research explores the evolution, future trends, and major collaboration patterns of international collaboration in the field of AI over the past 35 years. It also reveals the leading countries, core groups, and characteristics of collaboration in the field of AI.
- Artificial intelligence
- International collaboration
- Collaboration pattern
- Bibliometric analysis
- Social network analysis
- Open Access
Page range: 116 - 125
Changes in the world show that the role, importance, and coherence of SSH (social sciences and the humanities) will increase significantly in the coming years. This paper aims to monitor and analyze the evolution (or overlapping) of the SSH thematic pattern through three funding instruments since 2007.
The goal of the paper is to check to what extent the EU Framework Program (FP) affects/does not affect research on national level, and to highlight hot topics from a given period with the help of text analysis. Funded project titles and abstracts derived from the EU FP, Slovenian, and Estonian RIS were used. The final analysis and comparisons between different datasets were made based on the 200 most frequent words. After removing punctuation marks, numeric values, articles, prepositions, conjunctions, and auxiliary verbs, 4,854 unique words in ETIS, 4,421 unique words in the Slovenian Research Information System (SICRIS), and 3,950 unique words in FP were identified.
Across all funding instruments, about a quarter of the top words constitute half of the word occurrences. The text analysis results show that in the majority of cases words do not overlap between FP and nationally funded projects. In some cases, it may be due to using different vocabulary. There is more overlapping between words in the case of Slovenia (SL) and Estonia (EE) and less in the case of Estonia and EU Framework Programmes (FP). At the same time, overlapping words indicate a wider reach (culture, education, social, history, human, innovation, etc.). In nationally funded projects (bottom-up), it was relatively difficult to observe the change in thematic trends over time. More specific results emerged from the comparison of the different programs throughout FP (top-down).
Only projects with English titles and abstracts were analyzed.
The specifics of SSH have to take into account—the one-to-one meaning of terms/words is not as important as, for example, in the exact sciences. Thus, even in co-word analysis, the final content may go unnoticed.
This was the first attempt to monitor the trends of SSH projects using text analysis. The text analysis of the SSH projects of the two new EU Member States used in the study showed that SSH's thematic coverage is not much affected by the EU Framework Program. Whether this result is field-specific or country-specific should be shown in the following study, which targets SSH projects in the so-called old Member States.
- Text analysis
- Estonian Research Information System (ETIS)
- Slovenian Research Information System (SICRIS)
- Community Research and Development Information Service (CORDIS)
- Open Access
Page range: 126 - 136
We present an analytical, open source and flexible natural language processing and text mining method for topic evolution, emerging topic detection and research trend forecasting for all kinds of data-tagged text.
We make full use of the functions provided by the open source VOSviewer and Microsoft Office, including a thesaurus for data clean-up and a LOOKUP function for comparative analysis.
Through application and verification in the domain of perovskite solar cells research, this method proves to be effective.
A certain amount of manual data processing and a specific research domain background are required for better, more illustrative analysis results. Adequate time for analysis is also necessary.
We try to set up an easy, useful, and flexible interdisciplinary text analyzing procedure for researchers, especially those without solid computer programming skills or who cannot easily access complex software. This procedure can also serve as a wonderful example for teaching information literacy.
This text analysis approach has not been reported before.
- Topic evolution
- Emerging topics
- Text mining
- Open Access
Page range: 137 - 146
This paper aims to test the use of e-Lattes to map the Brazilian scientific output in a recent research health subject: Zika Virus.
From a set of Lattes CVs of Zika researchers registered on the Lattes Platform, we used the e-Lattes to map the Brazilian scientific response to the Zika crisis.
Brazilian science articulated quickly during the public health emergency of international concern (PHEIC) due to the creation of mechanisms to streamline funding of scientific research.
We did not assess any dimension of research quality, including the scientific impact and societal value.
e-Lattes can provide useful guidelines for different stakeholders in research groups from Lattes CVs of members.
The information included in Lattes CVs permits us to assess science from a broader perspective taking into account not only scientific research production but also the training of human resources and scientific collaboration.
- Zika virus
- Lattes Platform
- Brazilian research output
- Brazilian science
- Open Access
Page range: 147 - 150