Emerging Topics in Internet Technology: A Complex Networks Approach

TL;DR

This paper applies complex network analysis to bibliometric data from the Web of Science to identify emerging trends, influential works, and key themes in internet communication networks from 2014 to 2017.

Contribution

It introduces a novel complex network-based method for analyzing bibliometric data to uncover research trends and influential topics in internet technology.

Findings

High interest in social and computer networks clusters

Identification of key themes like communication and social networks

Detection of intellectual turning points in research evolution

Abstract

Communication networks, in general, and internet technology, in particular, is a fast-evolving area of research. While it is important to keep track of emerging trends in this domain, it is such a fast-growing area that it can be very difficult to keep track of literature. The problem is compounded by the fast-growing number of citation databases. While other databases are gradually indexing a large set of reliable content, currently the Web of Science represents one of the most highly valued databases. Research indexed in this database is known to highlight key advancements in any domain. In this paper, we present a Complex Network-based analytical approach to analyze recent data from the Web of Science in communication networks. Taking bibliographic records from the recent period of 2014 to 2017, we model and analyze complex scientometric networks. Using bibliometric coupling applied over complex citation data we present answers to co-citation patterns of documents, co-occurrence patterns of terms, as well as the most influential articles, among others, We also present key pivot points and intellectual turning points. Complex network analysis of the data demonstrates a considerably high level of interest in two key clusters labeled descriptively as "social networks" and "computer networks". In addition, key themes in highly cited literature were clearly identified as "communication networks," "social networks," and "complex networks".