M2. Analysis

back to the AIDA Toolbox
M1. Data Collection M2. Analysis M3. Communication

Recently, analysis of Bibliometric data has become easier than ever before with availability of (1) online analysis tools and (2) standalone software tools such as BibExcelCitNetExplorerCiteSpace IIHistCitePublish or PerishSci2 and VOSviewer.

Online Analysis Tools

Without any need to download data, you can analyse your research results in both Web of Science and Scopus platforms.

dzign-square-pay-per-click-campaign-management-internet-marketing-page  Scopus –  Analyze Search Results

dzign-square-pay-per-click-campaign-management-internet-marketing-page  Web of Science – Analyze Results

These tools allow you to quickly identify the top authors, countries, organizations, sources, etc.

Standalone Software Tools

Using the standalone bibliometric analysis tools you can perform various type of analysis including but not limited to the following.

  • Natural Language Processing and Extraction of Important Scientific Terms
  • Generating Term Maps
  • Generating Co-Authorship Maps
  • Generating (Co)Citation Maps

Among the existing tools, VOSviewer is recommended by the AIDA project due to its friendly and easy-to-use  user interface, and yet powerful features. CitNetExplorer is also recommended as a powerful tool specifically designed for analysis of Citation networks.

dzign-square-pay-per-click-campaign-management-internet-marketing-page  VOSviewer: [Tutorial] [Getting Started], [Download]

dzign-square-pay-per-click-campaign-management-internet-marketing-page  CitNetExplorer: [Getting Started], [Download]

Advanced Tools

dzign-square-pay-per-click-campaign-management-internet-marketing-page  Sci2 Tool: [Getting Started], [Download]

dzign-square-pay-per-click-campaign-management-internet-marketing-page  DFR-Browser: [Introduction], [Demo]

dzign-square-pay-per-click-campaign-management-internet-marketing-page  CiteSpace II: [How to use it], [Download]

 

if you need more help with Data Analysis please contact us.

AIDA: Automatic Identification of Research Trends