# Progress in the Knowledge, Application and Influence of Extremely Low Frequency Signals
## 2 Materials and Methods  
This paper studies all world scientific publications whose topic is ELF waves (0.3-300 Hz), indexed in the Scopus database. On the web, there are several search engines that are based on scientometric indicators such as the number and the quality of the contributions according to the metric of the magazine or the author. However, the results of these searches do not measure the relationships between the authors and the different collaboration communities that can be established [37]. From among the existing databases, Scopus has been selected, since it is the scientific database with the greatest contributions in publications worldwide [38].  
For the automatic obtaining of bibliographic data from the scientific publications of Scopus, an API (Application Programming Interface) asNetBot interface is used, developed by the research group of the engineering department of the University of Almeria (Spain) [39]. The extraction process can be divided into several stages:  
1. Obtaining information about documents that contain the established keywords initially contained in the summary, title, or keywords fields of the document.
2. Extracting the information of the authors of the works mentioned in step (1), including for each author the Scopus identification number of the author, affiliations, publications, dates, number of citations, and H-index.
3. Processing to obtain the collaborative network of authors who have published articles that contain the search keywords.  
For our search, TITLE-ABS-KEY \"ELF\" or \"extremely low frequency\" was used and many documents and relationships were obtained. The information obtained was analyzed using community detection algorithms and was plotted. Where the size of the nodes is proportional to the H-index, the lines between two nodes indicate that they are cited and the distance between them represents the collaboration between them. To carry out this representation an open source program, \"Gephi\" was used [40]. It covers several statistical tools for the treatment and visualization applying the community detection algorithm. This program allows the reorganization of the vertices or nodes, their design, and their representation with different sizes and colors according to their properties, among other possibilities. The results obtained show that it is possible to determine the main areas of research activity, as well as identify the structures of the collaborative network in the field of ELF waves. Gephi allowed the export with the appropriate filters to select the communities to study, and the key-id community pair was obtained from this process. Then a refinement and clustering of the keywords was applied to avoid typographical and punctuation errors. Among the most common mistakes was the distinction that doubles the number of words, according to upper- and lower-case letters, the singular and the plural, the separation of words with space or hyphen, etc.  
As a result of the large volume of data, some irregularities were observed during the information verification work--this problem is a frequent and common issue in the large databases and should be considered and corrected [41]. Thus, refinement is essential if you want to analyze the significant keywords used both globally and by community.  
Figure 1a shows the initial search result, where the information debugging process has not yet been carried out. This debugging eliminates unnecessary information in order to establish an overview, reducing the number of documents and their relationships. In the debugging process, documents that do not have a relationship with the communities were eliminated. This does not mean that they are not referenced by other authors, but rather that there are no collaboration ties, which is why they are deleted. This figure shows many documents on the periphery, which do not show connections with the main collaboration centers.