VOSviewer Visualization & Research Report Writing -- 5
Budget: $30 – $250 NZD
I have a corpus of scholarly records that needs to move from raw metadata to clear, publication-ready visuals—and then into a concise narrative that explains what those visuals mean. Using VOSviewer as the core tool, I want you to build high-quality network maps (co-authorship, co-citation, keyword co-occurrence—whatever yields the most insight), polish them for legibility, and wrap the results in a short research report that I can slot straight into a manuscript or presentation.
Here’s how I picture the flow:
• I hand over a CSV or RIS file exported from Scopus/Web of Science.
• You clean the data (duplicates, author name variations, etc.) and load it into VOSviewer.
• After configuring thresholds and clustering, you generate the main maps, tweak colors and labels, and export both high-resolution PNG/SVG and the interactive HTML version.
• Finally, you deliver a 2–3-page write-up that covers data preparation, visualization settings, and key findings (e.g., dominant research themes, leading authors, emerging clusters).
Acceptance criteria
– Visuals are crisp, cluster colors distinct, and labels readable at journal-print size.
– Report links each figure to a clear takeaway and includes enough methodological detail for replication.
– All source files (cleaned dataset and .vos files) are included so I can update the analysis later.
If you’ve wrangled bibliometric data before and can write a solid analytical narrative to match, I’d love to work with you.
Here’s how I picture the flow:
• I hand over a CSV or RIS file exported from Scopus/Web of Science.
• You clean the data (duplicates, author name variations, etc.) and load it into VOSviewer.
• After configuring thresholds and clustering, you generate the main maps, tweak colors and labels, and export both high-resolution PNG/SVG and the interactive HTML version.
• Finally, you deliver a 2–3-page write-up that covers data preparation, visualization settings, and key findings (e.g., dominant research themes, leading authors, emerging clusters).
Acceptance criteria
– Visuals are crisp, cluster colors distinct, and labels readable at journal-print size.
– Report links each figure to a clear takeaway and includes enough methodological detail for replication.
– All source files (cleaned dataset and .vos files) are included so I can update the analysis later.
If you’ve wrangled bibliometric data before and can write a solid analytical narrative to match, I’d love to work with you.