Abstract: The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.
Abstract: The production and publication of scientific works
have increased significantly in the last years, being the Internet
the main factor of access and diffusion of these. In view of this,
researchers from several areas of knowledge have carried out several
studies on scientific production data in order to analyze phenomena
and trends about science. The understanding of how research has
evolved can, for example, serve as a basis for building scientific
policies for further advances in science and stimulating research
groups to become more productive. In this context, the objective
of this work is to analyze the main research topics investigated
along the trajectory of the Brazilian science of researchers working
in the areas of engineering, in order to map scientific knowledge
and identify topics in highlights. To this end, studies are carried
out on the frequency and relationship of the keywords of the set of
scientific articles registered in the existing curricula in the Lattes
Platform of each one of the selected researchers, counting with the
aid of bibliometric analysis features.
Abstract: In spite of the global efforts toward gender equality, female researchers are still underrepresented in professional scientific activities. The gender gap is more seen in engineering and math-intensive technological scientific fields thus calling for a specific attention. This paper focuses on the Canadian funded researchers who are active in natural sciences and engineering, and analyses the gender aspects of researchers’ performance, their scientific collaboration patterns as well as their share of the federal funding within the period of 2000 to 2010. Our results confirm the existence of gender disparity among the examined Canadian researchers. Although it was observed that male researchers have been performing better in terms of number of publications, the impact of the research was almost the same for both genders. In addition, it was observed that research funding is more biased towards male researchers and they have more control over their scientific community as well.
Abstract: Every year, a considerable amount of money is being
invested on research, mainly in the form of funding allocated to
universities and research institutes. To better distribute the available
funds and to set the most proper R&D investment strategies for the
future, evaluation of the productivity of the funded researchers and
the impact of such funding is crucial. In this paper, using the data on
15 years of journal publications of the NSERC (Natural Sciences and
Engineering research Council of Canada) funded researchers and by
means of bibliometric analysis, the scientific development of the
funded researchers and their scientific collaboration patterns will be
investigated in the period of 1996-2010. According to the results it
seems that there is a positive relation between the average level of
funding and quantity and quality of the scientific output. In addition,
whenever funding allocated to the researchers has increased, the
number of co-authors per paper has also augmented. Hence, the
increase in the level of funding may enable researchers to get
involved in larger projects and/or scientific teams and increase their
scientific output respectively.
Abstract: Recently the use of data mining to scientific bibliographic data bases has been implemented to analyze the pathways of the knowledge or the core scientific relevances of a laureated novel or a country. This specific case of data mining has been named citation mining, and it is the integration of citation bibliometrics and text mining. In this paper we present an improved WEB implementation of statistical physics algorithms to perform the text mining component of citation mining. In particular we use an entropic like distance between the compression of text as an indicator of the similarity between them. Finally, we have included the recently proposed index h to characterize the scientific production. We have used this web implementation to identify users, applications and impact of the Mexican scientific institutions located in the State of Morelos.