OpenAlex Paper Search
Pricing
from $1.50 / 1,000 paper results
OpenAlex Paper Search
Search 250M+ scholarly works via the official OpenAlex API (CC0 data). Filter by year, open access, citations; get DOI, venue, citation counts and open-access PDF links as clean rows.
Pricing
from $1.50 / 1,000 paper results
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peti peti
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Search more than 250 million scholarly works (journal articles, preprints, books, datasets) and get clean rows with title, year, venue, citation count, DOI and a free open-access link when one exists.
Uses the official OpenAlex API. OpenAlex data is released under CC0 (public domain), so the results can be used in commercial projects, reports and datasets. No website is scraped.
Why use this instead of the API directly
- No code: fill a form, get a spreadsheet (CSV / Excel / JSON)
- Paging, retries and rate limits handled for you (up to 10,000 results per run)
- Nested API JSON flattened into one row per paper
- Easy to plug into Make, Zapier, n8n, or an LLM / RAG pipeline that needs paper lists with links
Input
{"query": "\"large language models\" education","sort": "relevance","fromYear": 2022,"openAccessOnly": true,"maxResults": 200}
| Field | Notes |
|---|---|
query | Use double quotes for exact phrases. |
searchIn | title_and_abstract (default, precise) or fulltext (broader). |
sort | relevance, citations (most cited), newest. |
fromYear / toYear | Publication year range. |
openAccessOnly | Only papers with a free legal copy. |
minCitations | e.g. 50 for well-known papers only. |
type | article, review, preprint, book, book-chapter, dissertation, dataset. |
language | ISO code such as en or ja. |
apiKey | Optional free OpenAlex key for bigger runs. |
Output (one row per paper)
{"openAlexId": "https://openalex.org/W4319460874","doi": "https://doi.org/10.1016/j.lindif.2023.102274","title": "ChatGPT for good? On opportunities and challenges of large language models for education","publicationYear": 2023,"publicationDate": "2023-03-09","type": "article","language": "en","venue": "Learning and Individual Differences","landingPageUrl": "https://doi.org/10.1016/j.lindif.2023.102274","citedByCount": 2500,"isOpenAccess": true,"openAccessStatus": "hybrid","openAccessUrl": "https://...","authors": ["Enkelejda Kasneci", "..."],"topic": "Artificial Intelligence in Education","field": "Social Sciences"}
(Values above are illustrative.)
Use cases
- Literature reviews: the 200 most cited papers on a topic, with free PDF links
- Market / technology research: what is being published on a subject each year
- Feeding a RAG system with paper metadata and open-access links
- Monitoring new papers weekly with a schedule and
sort: newest
What is not included
- Abstracts and full texts are not copied (publishers may hold the copyright). Follow
openAccessUrlorlandingPageUrlto read them. - Author contact details are not collected. Author names are included only as bibliographic metadata.
Pricing
Pay per event, platform usage included:
| Event | Price |
|---|---|
| Actor start | $0.01 per run |
paper-result – one paper returned | $1.50 per 1,000 papers |
Example: a search returning 200 papers costs $0.01 + $0.30 = $0.31.
Credits
Data from OpenAlex (Priem, J., Piwowar, H., & Orr, R. 2022, arXiv:2205.01833). This Actor is not affiliated with or endorsed by OpenAlex / OurResearch.
日本語での説明
公式 OpenAlex API(データは CC0 で商用利用可)を使って、2億5千万件以上の論文を検索し、タイトル・年・掲載誌・被引用数・DOI・無料で読めるリンクを表にして返します。サイトのスクレイピングはしません。要旨や本文はコピーしません。