Connected Papers For Non Profits: Research Literature Mapping
Connected Papers transforms a single academic paper into a visual map of related research—revealing connections you'd never find through keyword searches alone. Paste in one paper, and instantly see the 25-50 most conceptually similar studies arranged by similarity, publication year, and citation count. Free for up to 5 graphs per month.
What It Does
Found one great research paper but struggling to discover everything else relevant to your grant application or program design? Spending hours in Google Scholar following citation chains that lead nowhere?
Connected Papers builds a visual similarity graph around any academic paper you provide. Instead of showing you who cited whom (a citation tree), it uses co-citation and bibliographic coupling analysis to find papers that are conceptually related—even if they don't directly cite each other. Two papers studying the same phenomenon from different angles, using different terminology, will appear close together in your graph because other researchers frequently reference them in the same context.
The result is a visual map where node size shows citation count (bigger = more influential), node color indicates publication year (lighter = older, darker = newer), and proximity reveals conceptual similarity. You can quickly spot the seminal foundational work in a field, identify the latest cutting-edge research, and discover thematic clusters you never knew existed—all from a single starting paper.
Best For
Organization Size
- Small to mid-sized nonprofits doing occasional research
- Organizations with limited research budgets
- Academic-adjacent nonprofits and think tanks
Best Use Cases
- Quick literature discovery for grant proposals
- Exploring a new research area from a single known paper
- Identifying foundational and recent work in your cause area
- Building evidence bases for program design
Ideal For
- Grant writers needing evidence-based citations
- Program directors evaluating best practices
- Policy researchers conducting literature reviews
- Anyone who has one good paper and wants to find more like it
Key Features for Nonprofits
Visual Similarity Graphs
See how papers relate to each other at a glance—not just through citations
Connected Papers generates force-directed graphs where papers are positioned by conceptual similarity rather than direct citation links. This means two papers studying the same problem from different disciplines will cluster together, even if their authors have never cited each other. Visual cues make interpretation intuitive: larger nodes are more cited, darker nodes are more recent, and proximity indicates relatedness.
- Node size = citation count, so influential papers stand out immediately
- Node color = publication year, making it easy to spot historical vs. recent research
- Proximity = conceptual similarity, revealing thematic clusters and sub-fields
Prior & Derivative Works
Explore backwards to foundations and forwards to latest applications
Beyond the main similarity graph, Connected Papers provides two additional views. Prior Works shows papers frequently cited by the papers in your graph—the foundational research that shaped the field. Derivative Works shows newer papers that frequently cite the papers in your graph—the cutting-edge studies building on established knowledge. This bidirectional exploration helps you understand both the historical context and current trajectory of your research area.
- Prior Works surfaces foundational studies you should cite in grant proposals
- Derivative Works reveals how ideas are being applied in practice today
Multi-Origin Graphs
Build graphs from multiple seed papers for broader exploration
Premium users can create graphs using multiple origin papers, allowing you to explore the intersection of different research areas. This is valuable when your nonprofit's work spans multiple disciplines—for example, combining papers on mental health interventions with education outcomes research to find holistic approaches to youth development.
- Cross-disciplinary discovery by combining seed papers from different fields
- Broader coverage of your research area with multiple starting points
Filtering & List View
Narrow results by year, keyword, PDF availability, or open access
Switch between the visual graph and a sortable list view showing similarity percentages to your origin paper. Filter by publication year to focus on recent research, search for specific keywords within graph results, or filter for open-access papers only—particularly useful for nonprofits without university library access.
- Similarity percentages show exactly how related each paper is to your origin
- Open access filter helps find freely available papers without library subscriptions
How This Tool Uses AI
Connected Papers uses algorithmic analysis rather than deep learning or generative AI. Its strength lies in graph-based computational methods that identify paper relationships through citation patterns across the Semantic Scholar corpus.
What's Actually AI-Powered
🤖Co-Citation & Bibliographic Coupling Analysis
Type of AI: Graph-based similarity algorithms analyzing citation patterns across millions of papers
What it does: Measures the similarity between papers using two complementary methods. Co-citation identifies papers frequently cited together by other researchers (if many papers cite both A and B, they're likely related). Bibliographic coupling identifies papers that share many common references (if papers A and B both cite many of the same sources, they likely address related topics).
How it works: Combines co-citation and bibliographic coupling scores to produce a composite similarity metric, then uses force-directed graph algorithms to arrange papers spatially so that similar papers cluster together naturally
Practical impact: Discovers papers you'd never find through keyword searches—two studies on the same problem using completely different terminology will appear close together because the broader research community connects them through citation patterns
🤖Force-Directed Graph Visualization
Type of AI: Graph layout algorithms that compute optimal paper positions
What it does: Automatically positions papers in 2D space so that highly similar papers cluster together while dissimilar papers are pushed apart. The algorithm balances multiple forces to create clear, readable graphs where thematic clusters are visually obvious.
Practical impact: You can instantly see research sub-fields, identify bridge papers connecting different areas, and spot clusters of related work—tasks that would be impossible from a linear list of search results
What's NOT AI (But Still Useful)
- •Paper metadata lookup: Title, abstract, authors, and citation counts come directly from the Semantic Scholar database—standard database queries
- •Prior/Derivative Works: These are computed from direct citation relationships (who cites whom), not similarity algorithms
- •Filtering and sorting: Year filters, keyword search, and open access filtering are standard database operations
- •Saved graphs: Graph history and saved papers are traditional user account features
AI Transparency & Limitations
⚠️ Data Dependence
- •Limited by the Semantic Scholar index—coverage gaps exist for monographs, textbooks, and some non-English publications
- •Very new papers (published in the last 1-2 months) may not have enough citation data to appear in similarity graphs
- •Niche research areas with sparse citations produce less useful graphs
⚠️ Human Oversight Still Required
- •Similarity is based on citation patterns, not content quality—highly cited papers may be influential but flawed
- •The algorithm may miss relevant papers that use fundamentally different citation conventions
- •You still need to read and evaluate papers for relevance to your specific nonprofit context
🔒 Data Privacy
- ✓Your search queries and saved graphs are private to your account
- ✓Connected Papers analyzes publicly available citation data—no proprietary content is involved
- ✓You can view past graphs as many times as you like, even on the free plan
When AI Adds Real Value vs. When It's Just Marketing
Genuinely Useful
- •Similarity-based discovery finds related papers that keyword searches miss entirely
- •Visual clustering reveals research sub-fields and thematic groups at a glance
- •Prior/Derivative Works trace both the foundations and frontiers of a research area
❌ AI You Don't Need
- •If you already know exactly which papers you need, just search them directly in Semantic Scholar or Google Scholar
- •If your nonprofit doesn't use academic research, this tool won't add value—it's specifically for academic paper discovery
Bottom Line: Connected Papers uses well-established computational methods (co-citation analysis, bibliographic coupling, force-directed graphs) rather than trendy deep learning. This is an honest, no-hype approach—the algorithms do exactly what they claim, and they do it well. The tool excels at rapid visual discovery of related research, which is genuinely hard to accomplish manually.
Real-World Nonprofit Use Case
Youth Mentoring Organization Builds Evidence Base for Federal Grant
A youth mentoring nonprofit was applying for a federal grant that required an extensive literature review demonstrating evidence-based program design. Their program director had one landmark study on mentoring outcomes that she frequently cited, but the grant required at least 15-20 supporting references from peer-reviewed sources. Manually searching Google Scholar for "youth mentoring outcomes" returned over 50,000 results.
She pasted the landmark paper into Connected Papers and within seconds had a similarity graph showing the 40 most related studies. The visualization immediately revealed three distinct research clusters: one focused on academic outcomes, another on socio-emotional development, and a third on program design best practices. The largest nodes showed which studies were most influential in the field—exactly the papers funders would expect to see cited.
Using the Prior Works feature, she discovered foundational meta-analyses from the early 2000s that established the evidence base for mentoring interventions. The Derivative Works view surfaced recent 2024-2025 studies applying similar approaches in contexts matching her target population. She filtered for open-access papers (since her organization didn't have university library access) and found 12 freely available studies she could download immediately.
The entire process—from pasting the original paper to having a curated list of 20 relevant, credible references—took about 45 minutes instead of the 15+ hours she'd spent on manual searches for previous grants. She used 3 of her 5 free monthly graphs (one for her main topic, one for a related intervention approach, one for evaluation methodology) and didn't need to upgrade to a paid plan.
- Discovered 3 research clusters she hadn't known about, strengthening her literature review sections
- Found foundational meta-analyses that strengthened her evidence base significantly
- Completed literature review in 45 minutes vs. 15+ hours of manual searching
- Total cost: $0 (used 3 of 5 free monthly graphs)
Pricing
Free Plan
Enough for occasional research needs
- 5 graphs per month
- All features included
- View past graphs unlimited times
- Prior & Derivative Works
- Saved papers & graph history
Academic Plan
For academics, nonprofits, and personal use
- Unlimited graphs
- All features included
- Multi-origin graphs
- Nonprofits qualify for this tier
Business Plan
For business and industry use
- All Academic Plan features
- Unlimited graphs
- For-profit and commercial use
Note: Pricing information is subject to change. Please verify current pricing directly with Connected Papers.
Nonprofit Pricing & Discounts
Nonprofits Qualify for Academic Pricing
The Academic plan is explicitly designed for academics, nonprofits, and personal use. This means registered nonprofit organizations automatically qualify for the lower Academic tier ($3/month billed annually) rather than the Business tier ($10/month)—a built-in 70% discount compared to commercial pricing.
How to Access:
- 1.Sign up for a free Connected Papers account
- 2.When upgrading, select the Academic plan (intended for nonprofits)
- 3.Choose annual billing for the best rate ($3/month vs. $5/month quarterly)
Estimated Annual Savings: $84/year vs. Business plan pricing
Scholarship Program
For nonprofits and researchers who cannot afford even the Academic plan, Connected Papers offers a scholarship program providing discounted or free Premium access. Contact [email protected] to request consideration.
Group Plans
For teams needing multiple premium accounts, Connected Papers offers group plans. The Academic Group plan costs $5/seat/month (billed quarterly), allowing admins to assign premium access based on purchased seats.
Pro Tip: The free plan (5 graphs/month) is genuinely useful for most nonprofit research needs. If you only conduct research for 2-3 grant applications per year, the free tier may be sufficient. Test it first before upgrading.
Learning Curve
Beginner-Friendly
Overall Rating: Beginner
Connected Papers is one of the simplest research discovery tools available. Paste in a paper title, DOI, or URL, and you get a visual graph instantly. No account required to try it, no configuration needed, no complex settings to learn. The learning curve for basic use is essentially zero—interpreting the graphs effectively takes slightly longer, but the visual cues (size, color, proximity) are intuitive.
Time to First Value
Generate your first graph
Paste a paper and explore the visual similarity map
Effectively interpret graphs
Understand node size, color, proximity; explore Prior/Derivative Works
Master advanced features
Filtering, list view, multi-origin graphs, saved papers workflow
Technical Requirements
- No coding or technical skills required—paste a paper and explore
- Basic familiarity with academic papers helpful but not required
- Works in any modern desktop browser (Chrome, Firefox, Safari, Edge)
- Desktop recommended—not optimized for mobile devices or tablets
Support & Learning Resources
- About page with clear explanation of methodology and visual elements
- University library guides from institutions like University of Arizona and Loyola Marymount explain usage
- Medium blog with feature announcements and usage tips
- Email support via [email protected]
Integration & Compatibility
Connects With
Data Sources (Input)
- Semantic Scholar – Hundreds of millions of papers from all fields of science
- DOI – Paste any Digital Object Identifier
- arXiv, PubMed, Semantic Scholar URLs – Direct link input supported
- Paper titles – Search by title when you don't have a URL or DOI
Reference Management
- Paperpile – Third-party browser extension adds one-click import from Connected Papers results
- Zotero/Mendeley – No direct integration; manual export required
Notable Limitations
- No collaboration features—individual research tool only; no shared workspaces or team features
- No API access—cannot build custom integrations or workflows
- No monitoring/alerts—one-time graphs only, no automatic updates for new publications
Platform Availability
- Web-based (Chrome, Firefox, Safari, Edge) – No installation required
- Desktop – Works on Mac, Windows, Linux via web browser
- Mobile/tablet – Not optimized; graphs are difficult to navigate on small screens
- No dedicated mobile apps available
Pros & Cons
Pros
- +Incredibly simple—paste a paper, get a visual map instantly; zero learning curve for basic use
- +Free tier is genuinely useful—5 graphs/month with all features included covers most nonprofit needs
- +Nonprofits qualify for Academic pricing—only $3/month for unlimited graphs (billed annually)
- +Similarity-based discovery finds related papers that keyword searches miss entirely
- +Fastest tool for quick research snapshots—no setup, no configuration, instant results
- +Prior/Derivative Works provide both historical context and latest developments
- +Beautiful visualizations that can be shown to board members or included in presentations
- +Scholarship program available for those who can't afford premium plans
Cons
- −Limited to 5 graphs/month on free plan—heavy researchers will need to upgrade
- −No monitoring or alerts—one-time graphs only; won't notify you when new papers are published
- −No collaboration features—individual use only, can't share workspaces or work with colleagues
- −Limited integrations—no native Zotero/Mendeley support; only Paperpile via third-party extension
- −Desktop only—not optimized for mobile devices or tablets
- −Dependent on Semantic Scholar coverage—gaps for monographs, textbooks, and some non-English publications
- −Large graphs can be overwhelming—many nodes with complex connections can be hard to navigate
- −Less flexible than competitors—fewer customization options compared to Litmaps (can't adjust axes, node metrics, etc.)
Alternatives to Consider
If Connected Papers doesn't feel like the right fit for your nonprofit's research needs, here are comparable tools with different strengths:
Litmaps
Free tier available; Pro from $10/month (education) | More advanced with ongoing monitoring
Litmaps offers more advanced citation network visualization with customizable node metrics, multiple seed papers, overlapping maps for interdisciplinary research, and automatic literature monitoring alerts. It's more powerful but has a slightly steeper learning curve.
Choose Litmaps if:
- You need ongoing literature monitoring and alerts
- You want customizable visualizations and overlapping maps
- You conduct regular research across multiple topics
Choose Connected Papers if:
- You want the fastest, simplest tool with zero learning curve
- You do occasional research (5 or fewer graphs/month)
- You prefer simplicity over advanced customization
Semantic Scholar
100% Free | AI-powered academic search with TLDR summaries
Semantic Scholar (from nonprofit Allen Institute for AI) is a completely free AI search engine that provides paper summaries, citation analysis, and Research Feeds. It's text-based rather than visual, but offers TLDR summaries and broader search capabilities with no limits.
Choose Semantic Scholar if:
- You need unlimited, completely free searches
- You prefer text-based search over visual graphs
- You want AI-generated paper summaries (TLDRs)
Choose Connected Papers if:
- You want to visualize research relationships
- You want to discover related papers through similarity, not keywords
- You need to quickly identify influential vs. emerging studies
Scite
From $7.99/month | Smart Citations showing support/contradiction
Scite analyzes whether citations support or contradict a paper's claims—useful for evaluating research quality, not just finding related papers. It's more focused on citation context analysis than visual exploration.
Choose Scite if:
- You need to evaluate whether research supports or contradicts claims
- You're building evidence for policy advocacy or program evaluation
Choose Connected Papers if:
- You want visual exploration of research landscapes
- You want a free option for paper discovery
Why you might choose Connected Papers instead: Connected Papers is the fastest, simplest way to visually discover related research from a single starting paper. It requires zero setup, has a generous free tier, and produces immediately useful results. If your nonprofit needs quick literature discovery without the complexity of advanced research tools, Connected Papers is the best starting point.
Getting Started
Ready to discover research connections you've been missing? Here's how to get value from Connected Papers in under 15 minutes:
1Find Your Starting Paper (2 minutes)
Think of one academic paper you already know is relevant to your nonprofit's work. This could be a study you've cited in a grant proposal, a paper a colleague shared, or a foundational study in your cause area. You'll need either the paper title, its DOI, or a URL from Semantic Scholar, PubMed, or arXiv.
Don't have a specific paper? Search your topic on Google Scholar and pick the most-cited result as your starting point.
2Generate Your First Graph (1 minute)
Visit connectedpapers.com and paste your paper title or identifier into the search bar. The tool will generate a visual similarity graph showing the 25-50 most related papers.
- No account required to generate your first graph
- Click on any node to see paper details (title, abstract, authors, citation count)
3Explore the Graph (10 minutes)
Spend a few minutes exploring the visual graph and related features:
- Identify the largest nodes—these are the most influential papers in the field
- Look for clusters—groups of nearby nodes represent thematic sub-areas
- Check Prior Works—find the foundational studies that shaped this research area
- Check Derivative Works—see the latest research building on these ideas
- Use the list view—see similarity percentages and filter by year or open access
4Save and Build Your Evidence Base (Optional)
Create a free account to save your graphs and papers for future reference. Use the results to build your literature review:
- Save key papers to your Connected Papers library
- Generate additional graphs from the most relevant papers you discovered
- Use Paperpile integration for reference management (if applicable)
Next Step: Visit connectedpapers.com and paste in a paper you know—you'll see related research you never knew existed within 60 seconds.
Need Help with Implementation?
While Connected Papers is simple to use on its own, building a comprehensive evidence-based research workflow—choosing the right tools, integrating them with your grant writing process, and training staff on systematic literature review methods—can benefit from expert guidance.
One Hundred Nights offers support ranging from AI tool selection and setup to full-service research system design and staff training on evidence-based program development.
Contact Us to Learn MoreFrequently Asked Questions
Is Connected Papers free for nonprofits?
Connected Papers offers a free plan with 5 graphs per month that includes all features. For nonprofits needing unlimited graphs, the Academic plan ($3/month billed annually or $5/month billed quarterly) is specifically designed for academics, nonprofits, and personal use. There's also a scholarship program for those who can't afford a Premium plan—contact [email protected] to request discounted or free access.
How does Connected Papers differ from a citation tree?
Connected Papers creates similarity graphs, not citation trees. While a citation tree shows direct citation relationships (who cited whom), Connected Papers uses co-citation and bibliographic coupling to find conceptually similar papers. This means two papers can appear close together in the graph even if neither cites the other—they're connected because they share common references or are frequently cited together by other researchers. This approach often reveals more relevant research than following citation chains alone.
What database does Connected Papers use?
Connected Papers uses the Semantic Scholar corpus, which contains hundreds of millions of academic papers from all fields of science. You can input papers using DOI, arXiv URL, Semantic Scholar URL, PubMed URL, or paper title. Note that Semantic Scholar has some coverage gaps, particularly for monographs, textbooks, and some non-English publications.
Can I use Connected Papers on my phone?
Connected Papers is optimized for desktop browsers and may not work well on mobile devices or tablets. The visual similarity graphs require a larger screen for effective navigation and exploration. For the best experience, use a desktop or laptop computer with a modern browser like Chrome, Firefox, Safari, or Edge.
Does Connected Papers integrate with Zotero or other reference managers?
Connected Papers does not have direct native integrations with reference managers like Zotero or Mendeley. However, there is a third-party integration with Paperpile—the Paperpile browser extension adds a button to Connected Papers results, allowing one-click import of references and PDFs. For other reference managers, you would need to manually export data from Connected Papers.
How many papers does a Connected Papers graph show?
Each Connected Papers graph typically shows around 25-50 of the most similar papers to your origin paper. The graph isn't meant to be exhaustive—it highlights the most relevant and conceptually similar research. You can also view Prior Works (foundational papers cited by those in the graph) and Derivative Works (newer papers that cite the papers in the graph) for a more complete picture.