Ashkan Ebadi

How to become an important player in scientific collaboration networks

Scientific collaboration is one of the important drivers of research progress that supports researchers in the generation of novel ideas. Collaboration networks and their impact on scientific activities thus already attracted some attention in the research community, but no work so far studied possible factors which can influence the network positions of the researchers at the individual level. The objective of this paper is to investigate various characteristics and roles of the researchers occupying important positions in the collaboration network. For this purpose, we focus on the collaboration network among Canadian researchers during the period of 1996 to 2010 and employ multiple regression models to estimate the impact on network structure variables. Results highlight the crucial role of past productivity of the researchers along with their available funding in determining and improving their position in the co-authorship network. It is shown that researchers who have great influence on their local community do not necessarily publish high quality works. We also find that highly productive researchers not only have more important connections but also play a critical role in connecting other researchers. Moreover, although mid-career scientists tend to collaborate more in knit groups and on average have higher influence on their local community, our results specifically highlight the important role of young researchers who occupy mediatory positions in the network which enable them to connect different communities and fuel information transmission through the network.

How to Receive More Funding for Your Research? Get Connected to the Right People!

Funding has been viewed in the literature as one of the main determinants of scientific activities. Also, at an individual level, securing funding is one of the most important factors for a researcher, enabling him/her to carry out research projects. However, not everyone is successful in obtaining the necessary funds. The main objective of this work is to measure the effect of several important factors such as past productivity, scientific collaboration or career age of researchers, on the amount of funding that is allocated to them. For this purpose, the paper estimates a temporal non-linear multiple regression model. According to the results, although past productivity of researchers positively affects the funding level, our findings highlight the significant role of networking and collaboration. It was observed that being a member of large scientific teams and getting connected to productive researchers who have also a good control over the collaboration network and the flow of information can increase the chances for securing more money. In fact, our results show that in the quest for the research money it is more important how researchers build their collaboration network than what publications they produce and whether they are cited.

How to boost scientific production? A statistical analysis of research funding and other influencing factors

This paper analyzes the impact of several influencing factors on scientific production of researchers. Time related statistical models for the period of 1996 to 2010 are estimated to assess the impact of research funding and other determinant factors on the quantity and quality of the scientific output of individual funded researchers in Canadian natural sciences and engineering. Results confirm a positive impact of funding on the quantity and quality of the publications. In addition, the existence of the Matthew effect is partially confirmed such that the rich get richer. Although a positive relation between the career age and the rate of publications is observed, it is found that the career age negatively affects the quality of works. Moreover, the results suggest that young researchers who work in large teams are more likely to produce high quality publications. We also found that even though academic researchers produce higher quantity of papers it is the researchers with industrial affiliation whose work is of higher quality. Finally, we observed that strategic, targeted and high priority funding programs lead to higher quantity and quality of publications.

On the Relation between the Small World Structure and Scientific Activities

The modern science has become more complex and interdisciplinary in its nature which might encourage researchers to be more collaborative and get engaged in larger collaboration networks. Various aspects of collaboration networks have been examined so far to detect the most determinant factors in knowledge creation and scientific production. One of the network structures that recently attracted much theoretical attention is called small world. It has been suggested that small world can improve the information transmission among the network actors. In this paper, using the data on 12 periods of journal publications of Canadian researchers in natural sciences and engineering, the co-authorship networks of the researchers are created. Through measuring small world indicators, the small worldiness of the mentioned network and its relation with researchers’ productivity, quality of their publications, and scientific team size are assessed. Our results show that the examined co-authorship network strictly exhibits the small world properties. In addition, it is suggested that in a small world network researchers expand their team size through getting connected to other experts of the field. This team size expansion may result in higher productivity of the whole team as a result of getting access to new resources, benefitting from the internal referring, and exchanging ideas among the team members. Moreover, although small world network is positively correlated with the quality of the articles in terms of both citation count and journal impact factor, it is negatively related with the average productivity of researchers in terms of the number of their publications.

Impact of Funding on Scientific Output and Collaboration: A Survey of Literature

This document critically reviews the papers that investigated the impact of funding on scientific output and on scientific collaboration. For the output, the focus is on the number of articles as a measure of the scientific productivity and the number of citations that a paper received as an indicator of the quality. Various methodological approaches have been adopted (e.g. bibliometrics (a set of methods to analyse the scientific literature quantitatively), statistical analysis) for this purpose. Reviewing the literature revealed that although the general assumption of the positive effect of funding on scientific development is completely (or partially) acknowledged in some studies, one can also find some contradictory results. In addition, we note that analysing the impact of funding on scientific output has attracted more attention of the researchers while investigating the impact of funding on collaboration has been only recently taken into consideration. The paper concludes by comparing the major results and methodologies of the reviewed studies while highlighting the research gaps.

A network perspective of academiaindustry nanotechnology collaboration: A comparison of Canada and the United States

Novelty of nanotechnology and its invaluable application in almost all fields makes innovation in this sector an interest for many countries, including Canada and the United States. The collaboration between academia and industry is considered to be particularly beneficial in nanotechnology, as it is an emerging field where the science is interdisciplinary and applications are far and wide. This paper compares the nanotechnology innovation diffusion and knowledge transfer in Canada and the United States. In addition, it investigates the interaction between universities and industry in these countries and analyzes their network characteristics to highlight the distinct roles that academic and industrial researchers play in the collaboration network. The collaboration patterns are studied through co-authorship and co-inventorship data using social network analysis. The results show that the American nanotechnology subnetwork involves more collaboration, and is more centralized than the Canadian one. Moreover, in the aforesaid countries it was found that both academic researchers collaborating strictly within academia and industrial researchers working solely among themselves occupy more clustered but less central network positions. Consequently, no matter how productive or innovative these researchers are, their role in knowledge transmission is quite limited, while the researchers who bridge the two sectors through collaborations of university-industry nature are critical to the knowledge transfer through the network.

iSEER: an intelligent automatic computer system for scientific evaluation of researchers

Funding is one of the crucial drivers of scientific activities. The increasing number of researchers and the limited financial resources have caused a tight competition among scientists to secure research funding. On the other side, it is now even harder for funding allocation organizations to select the most proper researchers. Number of publications and citation counts based indicators are the most common methods in the literature for analyzing the performance of researchers. However, the mentioned indicators are highly correlated with the career age and reputation of the researchers, since they accumulate over time. This makes it almost impossible to evaluate the performance of a researcher based on quantity and impact of his/her articles at the time of the publication. This article proposes an intelligent machine learning framework for scientific evaluation of researchers (iSEER). iSEER may help decision makers to better allocate the available funding to the distinguished scientists through providing fair comparative results, regardless of the career age of the researchers. Our results show that iSEER performs well in predicting the performance of the researchers with high accuracy, as well as classifying them based on collaboration patterns, research performance, and efficiency.

Analyzing Scientific Activities of the Top Ten Canadian Universities

This paper investigates the impact of funding on scientific production of the researchers affiliated with the top Ten Canadian Universities. NSERC funding data in the period of 1996-2010 is considered, and the numbers of published articles in one-year and three-year time windows are counted as the proxy for the scientific production. In addition, we assess the impact of funding on quality of the funded researchers’ papers and their scientific team sizes.Results suggest a positive impact of funding on not only the quantity of the publications but also on the quality of the works and scientific team sizes of the funded researchers.