Name
Abstract | ||
|---|---|---|
Communication networks, in general, and Internet technology, in particular, are fast-evolving areas of research. The literature in these domains is expanding at such a fast scale that it is very difficult to understand the underlying dynamics and emerging trends. While several citation databases are gradually indexing a large set of reliable content, currently the Web of Science represents one of the most highly valued databases. 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 cocitation patterns of documents, cooccurrence 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." |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1002/itl2.41 | INTERNET TECHNOLOGY LETTERS |
Keywords | Field | DocType |
CiteSpace, communication networks, complex networks, data science, network science, visualization | Data science,Telecommunications network,Social network,Computer science,Citation,Search engine indexing,Complex network,Complex network analysis,The Internet | Journal |
Volume | Issue | Citations |
1 | 4 | 1 |
PageRank | References | Authors |
0.41 | 12 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bisma S. Khan | 1 | 1 | 0.75 |
| Muaz A. Niazi | 2 | 177 | 24.55 |