key: cord-1037145-jw5cuiip
authors: Zhang, Yi; Kajikawa, Yuya
title: Editorial: Advanced Analytics and Decision Making for Research Policy and Strategic Management
date: 2021-11-08
journal: Front Res Metr Anal
DOI: 10.3389/frma.2021.778622
sha: ee3b6ad6081fc1da7369a810a4dcb850df53b0c2
doc_id: 1037145
cord_uid: jw5cuiip

nan

Aiming to improve the performance of profiling the demographic characteristics of learners in the platform of Massive Open Online Course (MOOCs), Aljohani and Cristea developed a novel solution by incorporating certain state-of-theart deep learning models and architectures for text segmentation and analytics. Such demographic characteristics specifically focus on employment status and gender information.

While arguing the accessibility of traditional bibliometric data sources as well as nonspecific and outdated "global" measures, Hook and Porter facilitated the Dimensions database in the Google BigQuery Cloud environment and proposed a visualization solution for mapping institutions and their productivity in a geographical map.

With a specific interest in profiling COVID-19-related genetic research, Wu et al. proposed a solution exploiting a set of intelligent bibliometric models, such as scientific evolutionary pathways for tracking topic evolution and bio-entity network analytics for discovering gene-disease associations.

As a conclusion for this special topic, the topic editors and their colleagues particularly investigated topics and their evolutionary pathways in bibliometric research (Mejia et al.) .

In this study, the authors used several advanced bibliometric tools, such as citation network analytics, scientific evolutionary pathways, and hierarchical topic trees, to profile the keen interests of the bibliometric community and how such interests changes over time in the past decades.

With the four submissions in this collection, we observed that using, refining, and developing advanced analytic models, incorporating with state-of-the-art artificial intelligence and data science techniques, has become a rising trend in bibliometrics, and such a trend further adapts to actual needs from the community of research policy and strategic management, who are facing challenging issues on decision support in changing environments. Given that, we believe this special topic may feed readers with both novel methodological solutions and ingenious practical applications.

YZ and YK contributed to the editorial tasks of this special topic and this editorial.

Emerging Topics in Energy Storage Based on a Large-Scale Analysis of Academic Articles and Patents

Exploration of Shared Themes between Food Security and Internet of Things Research through Literature-Based Discovery

Extracting Commercialization Opportunities of the Internet of Things: Measuring Text Similarity between Papers and Patents

Profiling and Predicting the Problem-Solving Patterns in China's Research Systems: A Methodology of Intelligent Bibliometrics and Empirical Insights

Bi-layer Network Analytics: A Methodology for Characterizing Emerging General-Purpose Technologies

Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest