VOSviewer for Beginners: How to Create a Bibliometric Map from Scopus

• ⏱️ 10 min read • 📊 Bibliometrics • Research Visualization

Have you ever felt overwhelmed navigating thousands of journals for your research? Imagine being able to map topic trends, author collaboration networks, and keyword evolution in just a few minutes. That’s the power of bibliometric analysis, and VOSviewer is the free software that makes it as easy as drag-and-drop. VOSviewer was developed by the Centre for Science and Technology Studies (CWTS) at Leiden University and has become the gold standard among researchers worldwide. This article guides you step-by-step through exporting data from Scopus, processing it in VOSviewer, and generating publication-ready visual maps for reputable journals. If the process feels too complex or you want deeper bibliometric analysis, the Corvexum team is ready to help transform your raw data into high-quality publication insights.

Step 1: Export Data from Scopus

Scopus is the world’s largest indexed academic database with over 80 million records. To begin, search your research topic using precise Boolean queries. Once results appear:

  • Click the Export button at the top of the search results page.
  • Select CSV or RIS format (CSV is recommended for best VOSviewer compatibility).
  • Choose complete metadata: Citation information, Bibliographical information, Abstract & keywords, and References.
  • Click Export and save the file in your dedicated project folder.

Pro Tip: Limit results to the first 2,000 documents (Scopus maximum per export) to keep the map interpretable. For large datasets, use strategic sampling techniques.

Step 2: Import & Clean Data in VOSviewer

Open VOSviewer → click Create → select Create a map based on bibliographic data → choose Read data from bibliographic database files → locate your exported Scopus file.

VOSviewer will auto-detect the format. Select your analysis type based on your research objectives:

  • Co-authorship: Maps collaboration networks of researchers, countries, or institutions. Useful for international collaboration studies.
  • Co-occurrence: Displays keyword relationships (most popular for identifying research trends and emerging topics).
  • Citation: Citation networks between journals, documents, or authors for impact analysis.
  • Bibliographic coupling: Groups documents based on shared references.
  • Co-citation: Maps works that are frequently cited together.

Click Next until completion. Use Threshold to filter nodes that are too small or rarely appear (typically minimum 5 occurrences).

Step 3: Visualization & Map Interpretation

VOSviewer offers 3 powerful visualization modes:

  • Network Visualization: Circles (nodes) and lines (links). Node size = occurrence frequency, distance = relationship closeness, color = thematic cluster.
  • Overlay Visualization: Colors indicate average publication year. Extremely useful for tracking recent vs. classic trends. Yellow nodes = emerging topics, blue nodes = established topics.
  • Density Visualization: A heatmap highlighting the most concentrated research areas. Ideal for identifying research gaps.

Quick Interpretation: Same-color clusters = frequently co-discussed topics. Large nodes = dominant topics in the field. Thick lines = strong collaboration or co-occurrence. Isolated nodes = niche topics not yet widely explored.

Step 4: Deep Analysis with Data Tabs

Don’t just focus on visualizations! The Tables tab in VOSviewer provides crucial quantitative data:

  • Items tab: Complete list of nodes with occurrences, links, and total link strength.
  • Clusters tab: Node grouping into thematic clusters with automatic labels.
  • Score calculation: Calculates average publication year to identify emerging topics.

Combine this quantitative data with visualizations for a rich narrative in your research results chapter. Q1 journals like Scientometrics or Journal of Informetrics highly value this mixed-methods approach.

💡 Publication Pro Tip: Never screenshot your maps! Use Save → High resolution image (minimum 300 DPI) for reputable journals. Add legends, arrange labels to prevent overlap, and adjust the color scheme to match your target journal’s template.

🎯 Decision Framework: Which Analysis Type is Right?

  1. Topic exploration goal? → Use Co-occurrence with “Author keywords” as the unit of analysis.
  2. Collaboration mapping goal? → Use Co-authorship with “Countries” or “Organizations” as units.
  3. Landmark papers identification goal? → Use Citation analysis at the “Documents” level.
  4. Emerging topics detection goal? → Use Overlay Visualization + Average publication year score.

🚀 Ready for a Bibliometric Map That’s Q1/Q2 Journal-Ready?

Not every researcher has time to learn new software from scratch. Let us handle the entire technical process while you focus on strategic interpretation:

  • ✅ Automated Scopus/WoS/PubMed data export, cleaning, and mapping with verified pipelines
  • ✅ Topic trends, collaboration networks, and citation evolution analysis with deep interpretation
  • ✅ High-resolution exports (300+ DPI) + ready-to-paste narrative for Introduction or Literature Review chapters
  • ✅ Q1 journal publication strategy consultation in Scientometrics and Information Science fields
💬 Free Consultation via WhatsApp
📧 Send Data to Admin

Or email: corvexum@gmail.com | Visit: corvexum.com

Crafted by the Corvexum bibliometric research team to accelerate your academic literature review process. Share if helpful, and remember: strong research begins with a clear literature map.

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