Connected Papers

Force-directed graph visualizations where node proximity indicates conceptual similarity (via co-citation and bibliographic coupling), node size reflects citation impact, and color encodes publication recency. The algorithm processes a seed paper's citation context to identify the most conceptually related works and arranges them spatially so that tightly related papers cluster together while loosely related ones sit further apart. This visual encoding allows researchers to immediately grasp the structure of a research area, spot dominant clusters, identify bridge papers connecting subfields, and detect outlier works that might represent novel or underexplored approaches.

Three distinct visualization modes — similarity graphs, prior works graphs, and derivative works graphs — separate intellectual influences from subsequent impact. This creates a clear temporal narrative showing how ideas evolved from foundational theories to current applications. The prior works view traces backward through citation chains to reveal the theoretical and empirical foundations that shaped a paper's contributions, while the derivative works view maps forward to show how a paper's ideas have been extended, applied, challenged, or refined by subsequent research. Together these modes provide a complete intellectual genealogy for any indexed paper.

Premium feature on the $36/year Academic plan that allows seeding graphs with multiple papers simultaneously, identifying research at the intersection of different fields, methodologies, or theoretical frameworks. Particularly useful for interdisciplinary teams, this feature generates visualizations that highlight papers bridging disparate domains — for example, connecting computational neuroscience with clinical psychiatry, or linking machine learning methods with environmental science applications. The resulting graphs reveal synthesis opportunities and collaboration possibilities that single-origin searches would miss entirely.

Built on Semantic Scholar's 200M+ paper corpus with automated updates from arXiv, PubMed, IEEE, ACM, and major publishers. Provides broader coverage than tools relying on narrower citation indexes, with new papers typically indexed within days to weeks of publication. The integration leverages Semantic Scholar's natural language processing capabilities for metadata extraction and paper matching, ensuring high-quality citation linking even for papers from diverse sources. This extensive corpus forms the foundation for Connected Papers' graph algorithms, enabling comprehensive coverage across STEM disciplines and growing representation in social sciences.

Every generated graph receives a unique shareable URL for collaboration, and citation lists can be exported to BibTeX, RIS, and other reference manager formats. Integrates with Zotero, Mendeley, and EndNote workflows without requiring plugins or manual data entry. Researchers can share graph URLs with collaborators, advisors, or students to communicate their understanding of a research landscape visually. The export functionality allows seamless transition from discovery to citation management, enabling researchers to move selected papers directly into their reference libraries for use in manuscript preparation.