ANALYZING INTERNATIONAL COLLABORATION AND IDENTIFYING CORE TOPICS FOR THE “INTERNET OF THINGS” BASED ON NETWORK ANALYSIS AND TOPIC MODELING
DOI:
https://doi.org/10.23055/ijietap.2018.25.3.4194Abstract
The study of the “Internet of Things (IoT)” has been consistently evolving and rapidly expanding in the last decade. This research aims to examine the international collaboration among countries, identify major research areas and core topics in IoT-related studies, and exploit their relationships and dynamic changes over time. International collaboration is analyzed based on the collaboration ratio and centrality measures obtained from the collaboration network. To identify major research areas and core topics, we employ a two-layer approach: main research areas are determined by word co-occurrence analysis based on titles and author-provided keywords; core topics are found using a latent Dirichlet allocation (LDA), which is a well-known topic model that automatically discovers latent topics pervading a large collection of documents. We identify eight main research areas and 20 core topics from 8,582 research papers published from 2003 to 2015. Topic trends are also analyzed by modeling the topic proportions over time as a simple linear regression to determine hot and cold topics. A topic network integrating the discovered main research areas and core topics is also constructed to identify meaningful relationships among them. The findings of this study are expected to provide a summarized picture with helpful implications at a glance for academic researchers, industrial stakeholders, and governmental policy makers.Published
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