Who should use the Citation analysis workflow?
Teams or solo builders working on science & healthcare tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Science & Healthcare
Practical execution plan for citation analysis with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
A polished, actionable citation analysis report ready for presentation or publication.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
A polished, actionable citation analysis report ready for presentation or publication.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Keenious to a clean, structured dataset of citation records ready for analysis. Then, you pass the output to AI Excel Helper to a quantitative summary of citation impact with key performance indicators. Then, you pass the output to scite to a network map showing research fronts, influential papers, and thematic schools. Then, you pass the output to scikit-learn to a temporal map of topic evolution and emerging research directions. Then, you pass the output to scite to a ranked list of key contributors and a map of collaboration networks. Finally, Tableau AI is used to a polished, actionable citation analysis report ready for presentation or publication.
Data Collection and Source Selection
A clean, structured dataset of citation records ready for analysis.
Descriptive Citation Metrics Calculation
A quantitative summary of citation impact with key performance indicators.
Co-Citation and Bibliographic Coupling Analysis
A network map showing research fronts, influential papers, and thematic schools.
Thematic and Trend Analysis
A temporal map of topic evolution and emerging research directions.
Author and Institution Impact Mapping
A ranked list of key contributors and a map of collaboration networks.
Visualization and Report Generation
A polished, actionable citation analysis report ready for presentation or publication.
Identify the target publications, authors, or topics. Use bibliographic databases (e.g., Web of Science, Scopus, PubMed) to export citation data in structured formats (CSV, RIS, BibTeX). Ensure coverage of relevant time range and document types.
Why Keenious: Keenious provides contextual citation suggestions and bibliographic analysis, which aligns with the need for literature discovery and source selection in citation analysis.
Compute basic impact indicators: total citations, average citations per year, h-index, and citation distribution. Use spreadsheet formulas or dedicated bibliometric software (e.g., VOSviewer, Bibliometrix R package).
Why AI Excel Helper: AI Excel Helper can generate formulas and scripts for Excel/Google Sheets, which are commonly used for descriptive citation metrics calculations.
Identify intellectual structures by analyzing co-citation patterns (two papers cited together) and bibliographic coupling (shared references). Use network analysis tools to generate clusters and visualize relationships.
Why scite: scite is specifically designed for citation analysis and research discovery, directly supporting co-citation and bibliographic coupling analysis.
Extract key terms from titles, abstracts, and keywords. Perform burst detection to identify rising and declining topics over time. Use text mining or natural language processing (NLP) to generate term co-occurrence networks.
Why scikit-learn: scikit-learn provides classification, regression, and clustering algorithms (e.g., for topic modeling and trend detection), directly matching the need for Python-based thematic analysis.
Analyze productivity and collaboration patterns: identify top authors, institutions, and countries by citation count and collaboration strength. Use social network analysis to detect key brokers and research groups.
Why scite: scite provides citation analysis and research discovery, which can help map author and institution impact through citation networks.
Synthesize all findings into a coherent report with tables, charts, and network diagrams. Include executive summary, methodology, key metrics, thematic clusters, and actionable recommendations (e.g., potential collaborators, underexplored topics).
Why Tableau AI: Tableau AI provides data analysis, visualization, and predictive modeling, directly supporting the creation of visual reports for citation analysis.
§ Before you start
Teams or solo builders working on science & healthcare tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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