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CitationHub

Dataset Description

CitationHub is a large-scale scholarly citation dataset designed for citation analysis, citation intent modeling, scholarly knowledge graph construction, and evidence-grounded hypothesis generation for AI co-scientist systems.

The dataset contains citation events between citing papers and highly cited seed papers, enriched with citation intent labels, citation contexts, field information, journal metadata, author and affiliation information, and heterogeneous knowledge graph nodes and edges.

The dataset is intended to support research on:

  • Citation intent analysis
  • Scientific impact modeling
  • Future citation prediction
  • Scholarly knowledge graph completion
  • Intent-aware citation recommendation
  • Evidence-grounded hypothesis generation
  • AI co-scientist systems for scientific discovery

Dataset Repository: https://zenodo.org/records/18536895


Dataset Summary

File Rows Columns Description
citation_events.parquet 1,857,503 20 Raw citation event records
citation_events_enriched.parquet 1,857,503 32 Citation events enriched with cited seed paper metadata
citation_events_normalized.parquet 1,857,503 23 Citation events with normalized intent and field identifiers
citing_papers.parquet 1,467,045 7 Metadata of citing papers
citing_papers_normalized.parquet 1,467,045 8 Citing papers with normalized journal IDs
seed_cited_papers.parquet 23,479 42 Highly cited seed paper metadata
seed_cited_papers_normalized.parquet 23,479 48 Seed papers with normalized journal, author, affiliation, city, country, and field IDs
kg_edges.parquet 6,855,117 3 Heterogeneous knowledge graph edges
kg_nodes.parquet 3,418,433 14 Heterogeneous knowledge graph nodes
authors.parquet 16,839 2 Author ID-name mapping
affiliations.parquet 5,271 2 Affiliation ID-name mapping
affiliation_geo.parquet 5,352 6 Affiliation, city, and country mappings
journals.parquet 46,237 2 Journal ID-name mapping
fields.parquet 21 3 Field ID-name mapping
intents.parquet 31 2 Citation intent ID-name mapping
cities.parquet 1,899 2 City ID-name mapping
countries.parquet 108 2 Country ID-name mapping

Citation Events

The main citation event files contain paper-level citation relations and citation semantics.

Important fields include:

Field Description
citation_event_id Unique citation event identifier
citing_paper_id Identifier of the citing paper
cited_seed_paper_id Identifier of the cited seed paper
citing_doi DOI of the citing paper
citing_title Title of the citing paper
citing_year Publication year of the citing paper
citing_venue Venue of the citing paper
primary_intent Primary citation intent label
all_intents List of citation intents associated with the citation event
contexts Citation context text snippets
context_count Number of citation contexts
intent_count Number of intent annotations
is_influential Whether the citation is marked as influential
has_semantic_evidence Whether semantic evidence is available
field_id Normalized field identifier

Seed Cited Papers

Seed papers represent highly cited papers used as cited targets.

Important fields include:

Field Description
seed_paper_id Unique seed paper identifier
doi DOI of the seed paper
title Title of the seed paper
publication_name Publication venue
creator Main creator or first author
citedby_count Citation count
group Broad research group
category Research category
journal_clarivate Clarivate journal name
is_seed_top5pct Whether the seed paper belongs to the selected highly cited group

Knowledge Graph

The dataset includes a heterogeneous scholarly knowledge graph.

kg_nodes.parquet

Field Description
node_id Unique node identifier
label Human-readable node label
node_type Type of node
doi DOI if the node corresponds to a paper
publication_name Publication venue
group Research group
citedby_count Citation count
venue Venue information
year Publication year
primary_intent Citation intent for citation-event nodes

kg_edges.parquet

Field Description
source Source node ID
target Target node ID
edge_type Type of graph relation

Intended Uses

This dataset can be used for:

  1. Citation Intent Classification
  2. Future Citation Prediction
  3. AI Co-Scientist Hypothesis Generation
  4. Scholarly Knowledge Graph Completion
  5. Scientific Opportunity Discovery
  6. Citation-based Scientific Recommendation
  7. Evidence-grounded LLM Reasoning for Scientific Discovery

Dataset Construction

The dataset was constructed by integrating:

  1. Citation event records
  2. Citation contexts and citation intent labels
  3. Highly cited seed paper metadata
  4. Citing paper metadata
  5. Journal, author, affiliation, city, country, and field normalization tables
  6. Heterogeneous scholarly knowledge graph nodes and edges

The normalized files provide ID-based mappings for relational and graph-based experiments.


Dataset Structure

CitationHub/
├── affiliation_geo.parquet
├── affiliations.parquet
├── authors.parquet
├── citation_events.parquet
├── citation_events_enriched.parquet
├── citation_events_normalized.parquet
├── cities.parquet
├── citing_papers.parquet
├── citing_papers_normalized.parquet
├── countries.parquet
├── fields.parquet
├── intents.parquet
├── journals.parquet
├── kg_edges.parquet
├── kg_nodes.parquet
├── seed_cited_papers.parquet
└── seed_cited_papers_normalized.parquet

Ethical Considerations

This dataset is intended for scholarly analysis and research support. Citation-based metrics should not be used as the sole basis for evaluating researchers, institutions, journals, or countries.


Citation

@dataset{citationhub2026,
  title={CitationHub: An Intent-aware Scholarly Citation Knowledge Graph Dataset},
  author={Nam, Seohyun},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Daniel0315/CitationHub}
}

License

CC BY 4.0