Investigating the Relationship between Centrality Measures and Productivity of Persian Language and Literature Researchers

By Tajedini, Oranus; Shirazi, Narges et al. | Library Philosophy and Practice, December 2018 | Go to article overview

Investigating the Relationship between Centrality Measures and Productivity of Persian Language and Literature Researchers


Tajedini, Oranus, Shirazi, Narges, Sharifpour, Enayatollah, Library Philosophy and Practice


(ProQuest: ... denotes formulae omitted.)

Introduction

Over the past decades, the cooperation among individuals, research organizations and various countries to produce knowledge has been increasing. Scientific collaboration as an important activity facilitated the provision and dissemination of knowledge, and as a result, it attracted the researchers' attention (Ye, Li, & Law, 2011). In research context, co-authorship is the most observable and accessible indicator of scientific cooperation. A co-authorship social network represents the multidimensional relationships among researchers (e.g. colleagues) sharing their knowledge indirectly through publishing articles. This interconnected chain of relationships forms a kind of social network in which valuable resources are shared in the form of information, knowledge and awareness through social interactions. This network can provide its members with a joint capital, known as social capital. It has been proven that this capital has a positive effect on knowledge production and knowledge transfer. Members of co-authorship networks can benefit from the social capital through social interactions, broaden their horizons of awareness and seek better results (Jiang, 2008).

Analysis of social networks provides techniques for analyzing the structure of a network as a whole, as well as techniques for analyzing individual nodes and their locations in the network. The use of social network analysis as well as information visualization techniques enables researchers to identify the structural characteristics of co-authorship population, and the effective members of the population, to estimate the constraint and the efficiency of the network, and to determine the type of network. Therefore, by presenting the structure and studying a field of science cross-sectionally, the requirements of the field's development will be provided.

The analysis of social networks is based on the assumption that the relationship between social factors can be determined by drawing the corresponding graphs. The graph nodes represent social factors while the edges connect the pairs of nodes. Therefore, the graphs represent the social interactions between the nodes. These types of graphs provide researchers with the opportunity to use Mapping Theory to analyze issues, including the network of interconnected social relations of authors. Obviously, if this theory is not used, it is difficult to understand these relationships and interactions (Liu, et al., 2005).

The estimation of co-authorship in scientific publications is theoretically simple, and is significantly related to the degree of scientific cooperation. Collaboration can be useful for many reasons. It provides a great deal of ideas, methods and resources. It also facilitates sharing costs and saving time as a result of the division of labor (Lu & Feng, 2009). According to Cheong and Courbit (2009), numerous studies have highlighted the positive relation between scientific collaboration and co-authorship. Thus, co-authorship can be considered as one of the most convincing forms of research collaboration.

Given the positive effects of collaborative scientific activities, understanding these activities is very important because analyzing collaborative research activities from different perspectives and paying attention to their impact on scientific cooperation networks lead to a scientific understanding of the structure of research communities. For instance, National Institution for Academic Degrees and University Evaluation of Japan has accepted collaborative and scientific participation as an important point in the evaluation of research activities (Marin & Wellman, 2011). Research activities should be evaluated from a variety of perspectives, including the roles in scientific cooperation networks. Different perspectives may yield different results in research evaluation.

As mentioned, in analyzing co-authorship networks, ranking individuals in the social network, (i. …

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