You get:
- citing the same 5 classic papers everyone cites
- missing recent breakthroughs because they haven’t accumulated citations yet
- no sense of which scholars are currently active vs. retired
- wasting time on dead-end research fronts
- bibliographies that signal “I don’t know the field”
But citation networks reveal structure:
- seminal papers: high citation count, cited across many subfields
- hub papers: everyone in a specialty cites them
- bridge papers: connect two previously separate literatures
- frontier papers: recent, highly cited, signal where field is going
- outlier papers: cited but not part of main network (potential new direction)
Without network analysis, you cite what’s familiar, not what’s important.
This prompt analyzes a reference list or search results to map the citation landscape.
Assume the role of a bibliometric analyst who maps citation networks. Your task is to analyze a set of papers and identify the structure of the field. Generate: 1. SEMINAL PAPERS (the foundation) - Papers everyone cites - Why they matter (first study, theory, method, meta-analysis) 2. ACTIVE RESEARCH FRONTS (where the field is now) - Recent highly-cited papers (last 3-5 years) - What questions they're asking - What methods they're using 3. KEY RESEARCHERS - Senior scholars (long citation history) - Rising stars (recent high-impact papers) - Research groups/labs (multiple co-authored papers) 4. NETWORK STRUCTURE - Are there separate "camps" in this field? - Who bridges between camps? - What topics are peripheral vs. central? 5. GAPS IN YOUR CITATION LIST - Important papers you missed - Important scholars you missed - Alternative perspectives you haven't considered INPUTS: Reference list or search results: [PASTE BIBLIOGRAPHY OR SEARCH RESULTS] Your research topic: [E.G., "Remote work productivity"] Number of papers analyzed: [E.G., "25"] Time range: [E.G., "2000-2026"] RULES: - Use citation counts as signal, not gospel (recency bias, field size bias) - Flag self-citations (author citing own work repeatedly) - Distinguish between fields with different citation norms (humanities vs. STEM) - Note when a paper is cited for a finding vs. cited as a counter-example
- Start with 10-20 highly cited papers from Google Scholar on your topic.
- Extract their reference lists and feed them back in (snowball sampling).
- Look for papers cited by everyone in your field but not in your bibliography.
- Identify rising stars — they may be future collaborators or reviewers.
- Use the “active research fronts” to frame your contribution as timely.
Reference list or search results:
“1. Bloom et al. (2019) — 2,300 citations
2. Gibbs et al. (2021) — 890 citations
3. Choudhury et al. (2022) — 450 citations
4. Rockmann & Pratt (2015) — 1,200 citations
5. Golden (2006) — 3,100 citations
6. Allen et al. (2015) — 2,800 citations (meta-analysis)
7. Yang et al. (2024) — 120 citations”
Your research topic:
Remote work productivity
Number of papers analyzed:
7
This framework improves outcomes by forcing:
- seminal paper identification (foundation of the field)
- frontier detection (where the field is going)
- key researcher mapping (who to follow, cite, or email)
- network structure analysis (camps and bridges)
- gap detection (what you’re missing)
Great citation mapping doesn’t just list papers — it reveals the intellectual structure of a field.
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