| # | Cluster | Name | Papers | Strength | Citations | Avg Year | Country |
|---|
A research collaboration explorer powered by OpenAlex, the free and open academic publication database.
Search any researcher by name or ORCID to instantly map their co-authorship universe.
Type a researcher name or paste an ORCID iD and hit Search. CoAuthra fetches all their publications and builds a live network of collaborators — no account needed.
Click any node to highlight it and all its connections.
Right-click a node to open the author's OpenAlex profile.
Drag nodes to reposition. Scroll to zoom.
Click the canvas background to deselect.
By default only the top ~100 strongest collaborations are shown to keep the graph readable — the threshold is set automatically. Adjust in the sidebar:
• Min. shared papers — lower to reveal more collaborators.
• Year range & Work type — narrow by time or publication type.
• Institution — show only co-authors from specific institutions (appears after network loads).
• Topic clusters — filter by detected research community.
• Byline filter — show only papers where the searched author's listed affiliation matches their current institution, isolating collaborations built at a specific career stage.
All filters update stats, charts, and open access breakdown together.
Network — co-author graph sized by shared papers.
Citations — nodes sized by co-author total citations.
Funders — funding agency connections.
Geo — world map of collaboration countries.
Reveals direct connections between co-authors themselves, not just to the searched author. Uses community detection to cluster research groups visually — turning a star graph into a research community map. Toggle with the ★ Co-links button in the top-right toolbar. Purple dashed lines = co-author links. Lower Max links shown in the sidebar for cleaner cluster separation.
All publication and author data is fetched live from OpenAlex — a free, open academic graph cataloguing 474 million scholarly works. When you search a researcher, CoAuthra calls the OpenAlex REST API to retrieve their full publication list using cursor-based pagination (200 papers per request), then enriches each co-author with citation counts, institutions, and geographic data via batched author lookups.
Each paper's authorship list is parsed to extract co-authors. A co-author's shared paper count is the number of papers they appear on alongside the searched researcher. Link strength is a fractional weight — each paper contributes 1 / (number of co-authors), so papers with fewer authors create stronger ties. Co-authors are ranked by shared count and the top ~100 are shown by default to keep the graph readable.
The network is rendered using D3.js force simulation with a custom layout pipeline. Nodes are pre-positioned into cluster sectors before the simulation begins — so research communities start physically close together — then refined by charge repulsion, link attraction, and a cluster cohesion force that continuously pulls same-topic nodes toward their group centroid. This avoids the random sprawl of a naive force layout and produces spatially meaningful clusters from the first frame.
With Co-links enabled, direct co-author-to-co-author edges are computed from shared papers. The Louvain algorithm — a modularity-maximising community detection method — is run on this graph to assign cluster membership, grouping researchers who frequently collaborate with each other into the same colour cluster. With Co-links off, clusters fall back to the primary research topic of shared papers as reported by OpenAlex, keeping colours stable across filter changes.
Visualisation: D3.js v7 + TopoJSON. Graph layout: custom D3 force simulation with sector seeding and cohesion forces. Community detection: Louvain (implemented in JavaScript). Geographic map: D3 natural-earth projection.
All publication, authorship, citation, and institutional data displayed on CoAuthra is sourced exclusively from OpenAlex, a free and open academic publication database maintained by OurResearch. CoAuthra does not generate, modify, or independently verify any of this data. All records are retrieved live via the OpenAlex public API at the time of your search.
The data presented on this website may be incomplete, incorrect, or out of date. OpenAlex's coverage and accuracy varies by field, institution, and publication era. Author disambiguation, affiliation assignment, citation counts, and open access status are all computed algorithmically and may contain errors. CoAuthra presents this data as-is and makes no warranties regarding its accuracy, completeness, or fitness for any particular purpose.
The owner of this website and any organisations, institutions, or affiliations associated with the owner accept no responsibility or liability for the quality, accuracy, or completeness of data displayed on CoAuthra, nor for any decisions, actions, or consequences arising from its use. This tool is provided for informational and exploratory purposes only and should not be relied upon for official academic, professional, or legal purposes.
OpenAlex data is made available under the CC0 1.0 Universal (Public Domain) licence. Any concerns about data accuracy or missing records should be directed to OpenAlex directly. CoAuthra has no ability to modify or correct the underlying dataset.