A Review of Visibility Graph Analysis

Abstract

A graph approach to time series data provides a new perspective for analyzing and comprehending the characteristics of the data. One common method of converting time series into a graph is through visibility graph analysis. This technique has been developed and refined in various iterations over time. Moreover, visibility graph analysis has gained significant attention in recent years, with more than 88% of related articles published since 2016. Its applications span across multiple fields, including medicine, economy, geology, weather, architecture, and industrial processes. Accordingly, to conduct this research, a comprehensive collection of all articles in this field was obtained by searching the title, abstract, and keywords from Science Direct and Google Scholar databases. Finally, 249 related articles were gathered. These articles were then analyzed based on their publication year, field of application, network type, journal source, university affiliation, and other relevant factors. Through this examination process, unexplored areas with potential for future exploration were identified. Specifically, analyzing visibility graphs in security and service fields presents promising avenues for further investigation. Consequently, the study of visibility graph analysis offers valuable insights into time series data analysis. By understanding its applications across various disciplines and identifying untapped areas for research, we can expand our knowledge and contribute to advancements in this field.

Keywords

• Time series analysis
• visibility graph
• visibility graph analysis
• visibility graph classification
• complex network