Saeed-Ul Hassan

A bibliometric study of the world’s research activity in sustainable development and its sub-areas using scientific literature

This paper presents a bibliometric study of the world’s research activity in Sustainable Development using scientific literature. The study was conducted using data from the Scopus database over the time period of 2000–2010. We investigated the research landscape in Sustainable Development at country level and at institute level. Sustainable Development and its sub-areas are defined by keywords vetted by the domain experts, allowing publications to be identified independent of the journals and conferences in which they are published. The results indicate that institutes strong in Sustainable Development overall may not be strong in all sub-areas and that institutes not strong in Sustainable Development overall may have significant niche strengths in a given sub-area. It is also noted that China appears strong in terms of publication output in Sustainable Development and its sub-areas but it does not appear strong in terms of citation counts. The information produced in this study can be useful for government research agencies in terms of understanding how to more effectively knit together the various niche strengths in the country; and for the institutes to find strategic partners that can coordinate in niche areas of Sustainable Development and complement their strengths. In order to conduct bibliometric analysis in an interdisciplinary research area, the keyword collection approach appears to be very useful. This approach is flexible and can be used to conduct such analysis for interdisciplinary research fields.

Measuring international knowledge flows and scholarly impact of scientific research

We introduce a new quantitative measure of international scholarly impact of countries by using bibliometric techniques based on publication and citation data. We present a case study to illustrate the use of our proposed measure in the subject area Energy during 1996–2009. We also present geographical maps to visualize knowledge flows among countries. Finally, using correlation analysis between publication output and international scholarly impact, we study the explanatory power of the applied measure.

Robust hybrid name disambiguation framework for large databases

In many databases, science bibliography database for example, name attribute is the most commonly chosen identifier to identify entities. However, names are often ambiguous and not always unique which cause problems in many fields. Name disambiguation is a non-trivial task in data management that aims to properly distinguish different entities which share the same name, particularly for large databases like digital libraries, as only limited information can be used to identify authors’ name. In digital libraries, ambiguous author names occur due to the existence of multiple authors with the same name or different name variations for the same person. Also known as name disambiguation, most of the previous works to solve this issue often employ hierarchical clustering approaches based on information inside the citation records, e.g. co-authors and publication titles. In this paper, we focus on proposing a robust hybrid name disambiguation framework that is not only applicable for digital libraries but also can be easily extended to other application based on different data sources. We propose a web pages genre identification component to identify the genre of a web page, e.g. whether the page is a personal homepage. In addition, we propose a re-clustering model based on multidimensional scaling that can further improve the performance of name disambiguation. We evaluated our approach on known corpora, and the favorable experiment results indicated that our proposed framework is feasible.

A bibliometric study of research activity in ASEAN related to the EU in FP7 priority areas

Two relevant recent developments in the area of science and technology (S&T) and related policy-making motivate this article: first, bibliometric data on a specific research area’s performance becomes an increasingly relevant source for S&T policy-making and evaluation. This trend is embedded in wider discussions on evidence-based policy-making. Secondly, the scientific output of Southeast Asian countries is rising, as is the number of international research collaborations with the second area of our interest: Europe. Against this background, we employ basic bibliometric methodology in order to draw a picture of Southeast Asian research strengths as well the amount and focus of S&T cooperation between the countries in Southeast Asia and the European Union. The results can prove useful for an interested public as well as for the scientific community and science, technology and innovation policy-making.

Measuring recent research performance for Chinese universities using bibliometric methods

This paper focuses on measuring the academic research performance of Chinese universities by using Scopus database from 2007 to 2010. We have provided meaningful indicators to measure the research performance of Chinese universities as compared to world class universities of the US and the European region. Using these indicators, we first measure the quantity and quality of the research outcomes of the universities and then examine the internationalization of research by using international collaborations, international citations and international impact metrics. Using all of this data, we finally present an overall score called research performance point to measure the comprehensive research strength of the universities for the selected subject categories. The comparison identifies the gap between Chinese universities and top-tier universities from selected regions across various subject areas. We find that Chinese universities are doing well in terms of publication volume but receive less citations from their published work. We also find that the Chinese universities have relative low percentage of publications at high impact venues, which may be the reason that they are not receiving more citations. Therefore, a careful selection of publication venues may help the Chinese universities to compete with world class universities and increase their research internationalization.

A comprehensive examination of the relation of three citation-based journal metrics to expert judgment of journal quality

The academic and research policy communities have seen a long debate concerning the merits of peer review and quantitative citation-based metrics in evaluation of research. Some have called for replacing peer review with use of metrics for some evaluation purposes, while others have called for the use peer review informed by metrics. Whatever ones position, a key question is the extent to which peer review and quantitative metrics agree. In this paper we study the relation between the three journal metrics source normalized impact per paper (SNIP), raw impact per paper (RIP) and Journal Impact Factor (JIF) and human expert judgement. Using the journal rating system produced by the Excellence in Research for Australia (ERA) exercise, we examine the relationship over a set of more than 10,000 journals categorized into 27 subject areas. We analyze the relationship from the dimensions of correlation, distribution of the metrics over the rating tiers, and ROC analysis. Our results show that SNIP consistently has stronger agreement with the ERA rating, followed by RIP and then JIF along every dimension measured. The fact that SNIP has a stronger agreement than RIP demonstrates clearly that the increase in agreement is due to SNIPs database citation potential normalization factor. Our results suggest that SNIP may be a better choice than RIP or JIF in evaluation of journal quality in situations where agreement with expert judgment is an important consideration.

Small-world phenomenon of keywords network based on complex network

Based on the network comprised of 111,444 keywords of library and information science that are extracted from Scopus, and taken into consideration the major properties of average distance and clustering coefficients, the present authors, with the knowledge of complex network and by means of calculation, reveal the small-world effect of the keywords network. On the basis of the keywords network, the betweenness centrality is used to carry out a preliminary study on how to detect the research hotspots of a discipline. This method is also compared with that of detecting research hotspots by word frequency.

Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy

In this paper we propose a new technique to semantically analyze knowledge flows across countries by using publication and citation data. We start with the identification of research topics produced by a given source country. Then, we collect papers, published by the authors outside the source country, citing the identified research topics. At last, we group each set of citing papers separately to determine the scholarly impact of the actual identified research topics in the cited topics. The research topics are identified using our proposed topic model with distance matrix, an extension of classic Latent Dirichlet Allocation model. We also present a case study to illustrate the use of our proposed techniques in the subject area Energy during 2004–2009 using the Scopus database. We compare the Japanese and Chinese papers that cite the scientific literature produced by the researchers from the United States in order to show the difference in the use of same knowledge. The results indicate that Japanese researchers focus in the research areas such as efficient use of Photovoltaic, Energy Conversion and Superconductors (to produce low-cost renewable energy). In contrast with the Japanese researchers, Chinese researchers focus in the areas of Power Systems, Power Grids and Solar Cells production. Such analyses are useful for understanding the dynamics of the relevant knowledge flows across the nations.

Explaining the transatlantic gap in research excellence

The paper exploits a newly created dataset offering several detailed bibliometric data and indicators on 251 subject categories for a large sample of universities in Europe, North America and Asia. In particular, it addresses the controversial issue of the distance between Europe and USA in research excellence (so called “transatlantic gap”). By building up indicators of objective excellence (top 10% worldwide in publications and citations) and subjective excellence (top 10% in the distribution of share of top journals out of total production at university level), it is shown that European universities fail to achieve objective measures of global excellence, while being competitive only in few fields. The policy implications of this state of affairs are discussed.

The solitude of stars. An analysis of the distributed excellence model of European universities

The paper addresses the issue of the transatlantic gap in research excellence between Europe and USA by examining the performance of individual universities. It introduces a notion of leadership in research excellence by combining a subjective definition of excellence with an objective one. It applies this definition to a novel dataset disaggregated for 251 Subject Categories, covering the 2007–2010 period, based on Scopus data. The paper shows that European universities are able to show excellence only in a few disciplinary areas each, while US universities are able to excel across the board. It explains this difference in terms of institutional differences in recruitment process and governance of universities. It discusses the European model of distributed excellence in terms of the recent rise of input competition.