Connected Papers

Overview​

Connected Papers maps related academic literature as visual similarity graphs built from citation and reference relationships. It is effective for exploring a field and finding prior or derivative work, but it is not a citation tree, does not judge study quality and limits free graph creation.

Best for​

Literature discovery, visual field mapping, finding similar papers, locating prior and derivative work and expanding research reading lists

Pricing and availability​

The free tier includes a limited number of graphs each month. Academic, Business and group plans provide unlimited graphs, with commercial users expected to choose the Business plan and institutions able to request access.

Platforms and integrations​

Available through: web.

Users can start from a title, DOI, arXiv, PubMed or Semantic Scholar reference and open discovered papers in external scholarly services. There is no advertised general public API.

Privacy and security​

Accounts can store email, searches, settings and saved-paper lists, while third-party analytics collect usage data. Researchers should avoid treating graph proximity as evidence quality or causal relevance.

Key strengths​

• Visual graphs quickly reveal clusters around an origin paper
• Prior and derivative views help trace foundational and follow-up work
• Simple browser workflow is accessible to non-specialist researchers

Key limitations​

• Similarity does not evaluate methodology, credibility or study quality
• Free accounts are limited to a small number of monthly graphs
• Corpus gaps and citation bias can hide relevant or newer work

Editorial note​

CoinBotLab independently maintains this record using current provider documentation and independent sources. Features, pricing, availability and policies can change.