What is ResearchRabbit?
ResearchRabbit is an innovative research platform that revolutionizes how academics and researchers discover and manage scholarly literature. The platform employs an intelligent recommendation system similar to Spotify's approach, learning from users' collections to suggest relevant academic papers.
The platform features interactive network visualizations for exploring paper relationships and author collaborations, personalized email digests for staying updated with new publications, and collaborative tools for sharing collections. It integrates with Zotero and emphasizes a spam-free, quality-focused approach to research discovery.
Features
- Paper Collections: Create and organize collections of academic papers
- Smart Recommendations: AI-powered paper suggestions based on user interests
- Interactive Visualizations: Network graphs of papers and co-authorships
- Personalized Digests: Non-spammy email alerts for relevant new papers
- Collaboration Tools: Share collections and leave comments with other researchers
- Zotero Integration: Seamless integration with reference management
- Timeline View: Explore papers chronologically
Use Cases
- Literature review for academic research
- Discovering related papers in a research field
- Tracking new publications in specific research areas
- Collaborative research projects
- Academic paper organization and management
- Exploring author networks and collaborations
FAQs
-
How does ResearchRabbit recommend papers?
ResearchRabbit learns from your paper collections and reading preferences to suggest relevant academic papers, similar to how Spotify recommends music. -
Is ResearchRabbit completely free?
The platform offers a free version for researchers with core features, though some advanced features may require a subscription. -
Can I collaborate with other researchers on ResearchRabbit?
Yes, you can share collections with other researchers and leave comments, making it ideal for collaborative research projects.
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ResearchRabbit Uptime Monitor
Average Uptime
99.53%
Average Response Time
164.33 ms
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