Litmaps
AI citation network visualizer for academic research
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What is Litmaps?
Litmaps is a citation network visualiser designed to help researchers explore academic literature more effectively. Rather than reading papers in isolation, you can see how they connect to one another through citations, building a visual map of a research area. The tool uses AI to analyse citation networks and present relationships between papers in a way that's easier to handle than traditional search results. This is particularly useful when you're starting research in a new field and need to understand the landscape quickly, or when you want to find seminal papers and related work systematically. Researchers, PhD students, and academics can use Litmaps to identify key papers, track how ideas develop over time, and discover relevant work they might otherwise miss.
Key Features
Citation network visualisation
see how papers cite each other and understand research connections at a glance
AI-powered analysis
the tool identifies important nodes and relationships within citation networks automatically
Search and exploration
start with a paper or topic and explore outward through the citation graph
Map saving and sharing
create and organise citation maps for specific research projects
Integration with academic databases
connect to sources like PubMed, arXiv, and others to build networks
Filtering and navigation tools
drill down into specific areas of a citation network to focus your research
Pros & Cons
Advantages
- Reduces time spent on literature discovery by visualising connections you'd otherwise find manually
- Helps identify seminal papers and key research clusters in your field quickly
- Free tier offers meaningful functionality without requiring payment to start exploring
- Useful for understanding how research areas are structured and which papers influence others most
Limitations
- Quality of visualisations depends on the completeness of citation data in source databases; some fields may have better coverage than others
- Steep learning curve for building and interpreting complex networks effectively
- Free tier likely has limitations on map size, storage, or features compared to paid plans
Use Cases
Literature review: map out all papers related to your research question and identify gaps in existing work
Starting a new research project: understand the landscape of your chosen topic before diving into individual papers
Tracking research trends: see which papers are most cited and how research directions evolve over time
Identifying key authors: discover who the influential researchers are in a particular field or subarea
Writing a research proposal: visualise the current state of knowledge to position your work effectively