analyze_crossref_topic
Analyze a research topic's publication trends, top venues, publishers, funders, and most cited works by scanning Crossref for titles containing the exact phrase.
Instructions
Describe a research topic: publications per year, top venues, publishers and funders, and the
most cited works, counting only titles that contain the exact phrase.
When to use:
- Trend questions: "is X growing?", "when did X take off?", thesis/proposal background.
- "Where is X published?", "who funds X?" (venue and funder landscape).
How it works:
Crossref has no phrase search, so a plain query for "retrieval augmented generation" matches
about a million works. This tool scans the top `scan` relevance-ranked hits and keeps only
works whose title contains the exact phrase, then aggregates them. It is a sample of the most
relevant works, not a complete count; older years may be under-represented.
Args:
phrase: The topic phrase, e.g. "retrieval augmented generation" (hyphens/case ignored).
scan: Relevance hits to scan, 100-2000 (default 500). Larger = slower but more complete.
from_year: Optional earliest publication year.
until_year: Optional latest publication year.
work_type: Optional Crossref type, e.g. "journal-article".
Returns:
{"phrase", "fuzzy_total" (all keyword matches, for context), "scanned", "matched",
"per_year": {year: count}, "top_venues", "top_publishers", "top_funders": [[name, count]],
"most_cited": [compact work]}
Counts describe metadata only; they do not rank venue or funder quality.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| scan | No | ||
| phrase | Yes | ||
| from_year | No | ||
| work_type | No | ||
| until_year | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||