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The purpose of this paper is to present a novel approach for mining scientific trends using topics from Call for Papers (CFP). The work contributes a valuable input for researchers, academics, funding institutes and research administration departments by sharing the trends to set directions of research path.

The authors procure an innovative CFP data set to analyse scientific evolution and prestige of conferences that set scientific trends using scientific publications indexed in DBLP. Using the Field of Research code 804 from Australian Research Council, the authors identify 146 conferences (from 2006 to 2015) into different thematic areas by matching the terms extracted from publication titles with the Association for Computing Machinery Computing Classification System. Furthermore, the authors enrich the vocabulary of terms from the WordNet dictionary and Growbag data set. To measure the significance of terms, the authors adopt the following weighting schemas: probabilistic, gram, relative, accumulative and hierarchal.

The results indicate the rise of “big data analytics” from CFP topics in the last few years. Whereas the topics related to “privacy and security” show an exponential increase, the topics related to “semantic web” show a downfall in recent years. While analysing publication output in DBLP that matches CFP indexed in ERA Core A* to C rank conference, the authors identified that A* and A tier conferences not merely set publication trends, since B or C tier conferences target similar CFP.

Overall, the analyses presented in this research are prolific for the scientific community and research administrators to study research trends and better data management of digital libraries pertaining to the scientific literature.

The purpose of this paper is to analyze the scientific collaboration of institutions and its impact on institutional research performance in terms of productivity and quality. The researchers examined the local and international collaborations that have a great impact on institutional performance.

Collaboration dependence measure was used to investigate the impact of an institution on external information. Based on this information, the authors used “index of gain in impact through collaboration” to find the impact of collaborated publications in institutional research performance. Bibliographic data between 1996 and 2010 retrieved from Scopus were used to conduct current study. The authors carried out the case study of top institutes of Pakistan in terms of publication count to elaborate the difference between high performing institutions and those who gain disproportionally in terms of perceived quality of their output because of local or international collaboration.

The results showed that the collaboration of developing countries institutes on international level had a great impact on institutional performance and they gain more benefit than local collaboration. Altogether, the scientific collaboration has a positive impact on institutional performance as measured by the cumulative source normalized impact per paper of their publications. The findings could also help researchers to find out appropriate collaboration partners.

This study has revealed some salient characteristics of collaboration in academic research. It becomes apparent that collaboration intensity is not uniform, but in general, the average quality of scientific production is the variable that most often correlates positively with the collaboration intensity of universities.

This study aims to provide guidelines for exploring the research landscape in developing countries by gauging the prospects of growth, research impact and innovation. This study interrogates, analyses and visualizes the impact, nuances and evolution of stated research themes. For this purpose, this study presents an in-depth analysis of publications and citations indexed in Pakistani journals as a case study.

A bibliometric analysis of 46,034 publications published in Pakistan-based journals uncovers the research landscape of Scopus-indexed scientific literature – using various statistical and network-based approaches. Using VOSviewer and SPSS tools, the publication data has been analysed in relation to the open access status of papers, the number of authors, discipline, research theme and international co-authorship.

This study’s analyses reveal that while Pakistani journals are attracting international contributions from several countries, including India, Malaysia and Indonesia, no journal falls into the Scopus-defined top Quartile, i.e. the Q1 category. The analyses also highlight that only half (47%) of the publications received citations, whereas the other half remained uncited. Furthermore, open access publications received significantly higher citations than subscribed/traditional publications (print/online subject to toll access).

To the best of the authors’ knowledge, this is the first impact study of its kind that critically analyses the research landscape of Pakistani journals, especially in the context of the efforts of the higher education commission of Pakistan to promote research culture in the country. This study also provides analytical insights and policy guidelines for improving the quality of research published in Pakistani journals. This study can be replicated for other developing nations to provide guidelines and sustainable pathways for scientific growth in pursuit of uplifting nations by allocating resources for developing science and technology.

The latest developments in Data Science and in advanced Scientometrics set a very challenging context for the analysis and the understanding of human behavior toward the design of value adding library services and sophisticated information systems. The purpose of this paper is to present an innovative research that integrates the creation and the consumption of scientific knowledge across regions. From a human behavior point of view, this is significant since it provides an advanced decision-making layer for bringing together researchers from all over the world.

More specific in this paper, the authors analyze the production and consumption of scientific knowledge across the regions in an important field of sustainable and renewable energy – using publications and citations data indexed in Scopus. As a case study, the authors select the USA a major producer of scientific publications in the field. At first, the authors identify the topics produced by the USA. Further topics produced by the scientific communities outside the USA that consume the knowledge produced by the USA are identified. The authors generate topics by employing the proposed topic model with distance matrix – an extension of classic latent Dirichlet allocation model.

The results show that research topics produced by the USA are consumed in different international contexts, interestingly. Consuming the knowledge produced by the USA, Chinese scientific community heavily produces topics related to biomass – to produce renewable energy. In contrast, Japanese scientific community produces topics related to fuel cell – used for the production of hybrid and electronic vehicles. Whereas the Taiwanese scientific community shows remarkable competency in solar cells. Among the European nations, while the German scientific community produces topics related to photovoltaic, the French scientific community covers topics related to Energy Storage and Green Chemistry. The authors believe that such analyses may be helpful in establishing more effective multi-national research collaborations by understating the actual consumption of produced knowledge.

Overall, the study provides a new dimension to comprehensively understand production and consumption of knowledge using scientific literature. From a human behavior analysis view in the context of sophisticated library systems, this is a significant contribution.

The use of advanced Data Mining and computing methods for deriving critical insights for the use of scientific knowledge is a bold action toward the global knowledge society vision.

The Belt and Road Initiative (BRI) – the modern equivalent of the historic Silk Route – will connect China to multiple countries in Asia, Africa, and Europe through a complex web of land and sea routes. As a pilot project of a network of this magnitude, the 62 billion dollar China Pakistan Economic Corridor (CPEC) has far-reaching implications for future bilateral agreements with other countries along the routes, and for geopolitics in the region. This chapter will analyze CPEC along the following key strands of inquiry: Pakistan’s internal political economy, her macroeconomic stability, and an analysis of the corridor’s long-term impact.

While the literature on corridors is extensive, it does not give us a unifying theory with which to gauge the effectiveness of CPEC, which is more than an economic endeavor. In order to truly understand the dynamics of the region, the authors examine the extent to which domestic support for the CPEC may impact the whole initiative, and how the deficiencies in local infrastructure may take away from its success.

In as much as it is contested, the Belt and Road Initiative (BRI) is also unexplored, underdiscussed, and, as a result, misunderstood. Frequently viewed through the lens of international relations and global economy, the diverse dimensions of collaboration, including business and research-industry clusters, that BRI enhances, tend to be excluded from the analysis. In a similar manner, the role of the Arab Peninsula in the grand strategy underpinning BRI and its implementation is rarely discussed. BRI is a forward-oriented initiative, an attempt to reap benefits of developments and circumstances that are only nascent. This bears two potent implications. First, as China attempts to influence the context in which it operates, it is subject to change itself; the Chinese business sector evolution attests to that. Second, some of China’s not so obvious partners of today, including those in the Arab Peninsula, are about to turn into key interlocutors of tomorrow. BRI taps into opportunities thus created. This chapter elaborates on these issues and, against this backdrop, outlines how the remaining chapters included in this volume add to this discussion.

Degree apprenticeships in the UK have grown exponentially since they were introduced. While claims and speculations about their impact have been made by high-profile politicians, lobbyists and training providers, the evidence base for these claims has never been systematically scrutinised. The purpose of this paper is to analyse and present up-to-date peer-reviewed evidence on the impact of degree apprenticeships on social mobility and productivity and their influence on future policy.

The authors critically and systematically review over 4,000 data points from relevant sources and synthesise the results qualitatively and quantitatively with a combined method approach. Quantitative evidence has been aggregated where possible and tested for statistical significance. Qualitative evidence has been critically reviewed and comparatively analysed.

The analysis reveals that there is a shortage of depth and breadth of concrete and peer-reviewed evidence on the impact of degree apprenticeships. Nevertheless, existing data demonstrate that degree apprenticeships are meeting their intended purpose of contributing positively to the UK Government’s high-level goals for productivity and social mobility. They are an alternative route into higher education and serve as a vital talent pipeline providing opportunities for young people, existing employees and learners from diverse backgrounds.

This paper provides the first systematic and peer-reviewed synthesis of the impact of degree apprenticeships. It brings together existing evidence and statistically validates outcomes to inform researchers, educators, training providers, policymakers and other stakeholders in their recommendations moving forward.

How to extract useful information from a very large volume of literature is a great challenge for librarians. Topic modeling technique, which is a machine learning algorithm to uncover latent thematic structures from large collections of documents, is a widespread approach in literature analysis, especially with the rapid growth of academic literature. In this paper, a comparison of topic modeling based literature analysis has been done using full texts and abstracts of articles.

The authors conduct a comparison study of topic modeling on full-text paper and corresponding abstract to assess the influence of the different types of documents been used as input for topic modeling. In particular, the authors use the large volumes of COVID-19 research literature as a case study for topic modeling based literature analysis. The authors illustrate the research topics, research trends and topic similarity of COVID-19 research by using Latent Dirichlet allocation (LDA) and topic visualization method.

The authors found 14 research topics for COVID-19 research. The authors also found that the topic similarity between using full-text paper and corresponding abstract is higher when more documents are analyzed.

First, this study contributes to the literature analysis approach. The comparison study can help us understand the influence of the different types of documents on the results of topic modeling analysis. Second, the authors present an overview of COVID-19 research by summarizing 14 research topics for it. This automated literature analysis can help specialists in the health and medical domain or other people to quickly grasp the structured morphology of the current studies for COVID-19.