Social network analytics for advanced bibliometrics: referring to actor roles of management journals instead of journal rankings

Abstract

Impact factors are commonly used to assess journals relevance. This implies a simplified view on science as a single-stage linear process. Therefore, few top-tier journals are one-sidedly favored as outlets, such that submissions to top-tier journals explode whereas others are short of submissions. Consequently, the often claimed gap between research and practical application in application-oriented disciplines as business administration is not narrowing but becoming entrenched. A more complete view of the scientific system is needed to fully capture journals ´ contributions in the development of a discipline. Simple citation measures, as e.g. citation counts, are commonly used to evaluate scientific work. There are many known dangers of miss-or over-interpretation of such simple data and this paper adds to this discussion by developing an alternative way of interpreting a discipline based on the positions and roles of journals in their wider network. Specifically, we employ ideas from the network analytic approach. Relative positions allow the direct comparison between different fields. Similarly, the approach provides a better understanding of the diffusion process of knowledge as it differentiates positions in the knowledge creation process. We demonstrate how different modes of social capital create different patterns of action that require a multidimensional evaluation of scientific research. We explore different types of social capital and intertwined relational structures of actors to compare journals with different bibliometric profiles. Ultimately, we develop a multi-dimensional evaluation of actor roles based upon multiple indicators and we test this approach by classifying management journals based on their bibliometric environment.

Profiling and predicting the problem-solving patterns in China’s research systems: A methodology of intelligent bibliometrics and empirical insights

“…Along with the engagement of new data sources and indicators, such as technology opportunity analysis (Ma, Porter et al, 2014) 1 , technology roadmaps (Li, Zhou et al, 2015), and triple helix models to describe university-industry-government collaborations (Leydesdorff & Zhou, 2014;Zhang, Zhou et al, 2014b), the interactions between bibliometrics and information technologies are increasing. In turn, bibliometric solutions are becoming more effective: for example, large-scale data analytics and mapping (Börner, Klavans et al, 2012;Boyack, Newman et al, 2011), accurate knowledge extraction and representation (Zhang, Wan et al, 2018a;Zhang, Zhang, & Li, 2019a), full-text analytics (Boyack et al, 2018), and social network analytics (Rost, Teichert, & Pilkington, 2017;Yan & Guns, 2014). Driven by diverse practical needs, incorporating computational models, particularly artificial intelligence techniques, with bibliometric indicators and approaches is spearheading new research frontiersfor example, information visualization enhances the ability and adaptability of decision support (Chen, 2006;Waltman, van Eck, & Noyons, 2010).…”

“…Driven by diverse practical needs, incorporating computational models, particularly artificial intelligence techniques, with bibliometric indicators and approaches is spearheading new research frontiersfor example, information visualization enhances the ability and adaptability of decision support (Chen, 2006;Waltman, van Eck, & Noyons, 2010). This research route moves forward either by developing more effective algorithms, approaches, and tools for visualization (Chen & Song, 2019;Ping & Chen, 2018) or by facilitating network analytics to uncover latent relationships by analyzing the topological structures of science maps (Rost et al, 2017;Zhang, Wang et al, 2018c). Specifically, SAO analysis with the capability of understanding syntax from sentences has received great attention from the communities of bibliometrics and technology management.…”

Bridging the relevance-ranking chasm: mission impossible?

“…Although promising in terms of the satisfactory nature of their results, they conclude that this is still somewhat of a time consuming and intensive experience because of the extent of manual intervention the process warranted. Rost et al, (2017) argue that while bibliometric measures such as citation counts are useful, a more nuanced understanding of them is needed, in that frequency of citation needs to be complemented by an understanding of where the article has been cited. This suggests that the environment of citation needs consideration and is particularly important for interdisciplinary research because a core set of journals that form the environment cannot be easily identified.…”

“…This suggests that the environment of citation needs consideration and is particularly important for interdisciplinary research because a core set of journals that form the environment cannot be easily identified. Rost et al, (2017) contend that this one-dimensional approach is limiting and propose instead a methodology that incorporates social network analysis and thereby facilitates identification of the roles that journals play. Such a methodology and measures have potential to increase our understanding about the nuances of citation, e.g.…”

Social Capital, Human Capital, and Sustainability: A Bibliometric and Visualization analysis

“…Other bibliometric studies analyze research on social capital related to management [16], communication, [17], sociology [18], or academic careers [19]. In addition, some bibliometric studies focus on human capital [20] or related areas such as non-financial information [21] and human capital in university research centers [22].…”