CNKI Scraper: 中国知网 Citations, Rankings & Academic Search

Search China's largest academic database without reading a word of Chinese Get structured CNKI (中国知网) paper records, citation counts, and journal-prestige tiers in one clean dataset. No login, no API key, no account.

🏆 Journal-tier filtering Filter to 北大核心, CSSCI, CSCD, and more, a distinction Google Scholar never shows you

📊 Real citation data Every result carries its real citation and download counts, ready to sort and rank

🔔 New-paper & citation alerts Save a search or a paper list and hear about it only when something actually changes

🔓 No login, ever Every field comes from CNKI's own public paper pages, no account required

🔍 What does CNKI Scraper do?

CNKI Scraper searches CNKI (中国知网), China's largest academic and journal database, and returns clean, structured bibliographic records instead of raw web pages. For each paper you get the title, authors, abstract, keywords, DOI, journal or source, publication date, database type, citation count, download count, and journal-prestige tier.

This actor covers citation-level metadata only. It does not download full-text articles or PDFs, that content sits behind CNKI's own paid login and stays out of scope entirely. What it does cover, it covers well: everything a researcher, a due-diligence reviewer, or a data pipeline actually needs to evaluate a paper without reading it end to end.

Run it on demand from the Apify Console or API, or schedule it to watch a topic over time.

💡 Why use CNKI Scraper?

"I need every Chinese-language paper on my topic, not just the fraction Google Scholar happens to index." Most of CNKI's corpus barely shows up in Western search tools. This actor searches CNKI directly, by keyword, author, subject, or classification code, and hands back structured records you can filter, sort, and export.

"Before we sign off on a research partnership, I need to see this scholar's real publication record." University research-security and international-collaboration offices use this actor to pull a researcher's papers, citation counts, and journal tiers in one pass. A record built entirely on low-tier venues looks very different from one anchored in 北大核心 or CSSCI journals, and that difference is exactly what this actor surfaces.

"I need clean title, abstract, and keyword data at scale, not a scraper I have to build myself." AI and RAG teams building Chinese-language academic corpora get structured, ready-to-embed records straight out of the dataset, no HTML parsing required.

Two things Google Scholar and Web of Science-style tools don't offer for the Chinese corpus: journal-prestige tier filtering, and a clean split between journals, theses, conferences, newspapers, and other database types instead of one blended result list.

🚀 How to use CNKI Scraper

STEP 1 Choose your search Pick keyword, author, subject, or classification code, then set database, discipline, tier, and date filters.

STEP 2 Run the actor Get papers, citation rankings, author profiles, and a corpus breakdown in four ready-made dataset views.

STEP 3 Turn on monitoring Schedule the actor to flag newly indexed papers, or track citation-count changes on a saved paper list.

Every run works out of the box with the default input, no configuration required to get your first results.

📥 Input

Field	Type	Required	Description
searchMode	enum	No	Which CNKI field to search: keyword, author, subject, or classification code
query	string	Yes*	The search term, matched against the field searchMode selects
databaseTypes	array of enums	No	Restrict to specific database types (academic journals, theses, conferences, newspapers, and more)
discipline	string	No	Free-text subject discipline, matched against CNKI's live discipline list for your query
journalTiers	array of enums	No	Restrict to one or more journal-prestige tiers (北大核心, CSSCI, CSCD, AMI, WJCI, EI, SCI)
dateFrom	date	No	Only include papers published on or after this date
dateTo	date	No	Only include papers published on or before this date
language	enum	No	Restrict results to Chinese, English, or any language
includeCitationString	boolean	No	Add a ready-to-use GB/T 7714 citation string to each result
includeAuthorProfiles	boolean	No	Fetch each paper's institution data and populate the Author Profiles view
maxResults	integer	No	Maximum papers to return per run (up to 50, see FAQ for why)
sortBy	enum	No	Order results by relevance, publication date, cites, downloads, or overall
onlyNewOrChanged	boolean	No	Monitor mode: report only papers not seen in a previous run
stateName	string	No	Names the persisted state for monitor mode and citation tracking
trackCitationChanges	boolean	No	Switch to citation-tracking mode for a saved list of papers
savedPapers	array of objects	No	Papers to re-check when trackCitationChanges is on
resetState	boolean	No	Clear persisted monitor or citation-tracking state before this run

* Required unless trackCitationChanges is on with a saved paper list.

📤 Output

{
  "paperId": "vYTWSbYGSQp3w6reOAI3lj3RnWXwYoFkLC4heEcK98Jk...",
  "title": "Challenges and Prospects for Constructing the New-type Power System Towards a Carbon Neutrality Future",
  "authors": ["张智刚", "康重庆"],
  "source": "Proceedings of the CSEE",
  "publicationDate": "2022-04-20",
  "databaseType": "Journals",
  "cites": 2722,
  "downloads": 36875,
  "hasChineseFullText": true,
  "hasEnglishMT": true,
  "citationString": "张智刚, 康重庆. Challenges and Prospects for Constructing the New-type Power System Towards a Carbon Neutrality Future. Proceedings of the CSEE, 2022.",
  "sourceUrl": "https://oversea.cnki.net/kcms2/article/abstract?v=..."
}

You can download the dataset in JSON, CSV, Excel, HTML, or XML from the Output tab, or pull it through the API.

📋 Data table

Field	Type	Description
title	string	Paper title, cleaned of CNKI's display artifacts
authors	array of strings	Author names in publication order
source	string	Journal, conference, or publication source name
publicationDate	string	Publication date as shown by CNKI
databaseType	string	Journals, Theses, Conferences, Newspapers, and other CNKI database types
cites	number	Citation count at time of scraping
downloads	number	Download count at time of scraping
hasChineseFullText	boolean	Whether a Chinese full-text version exists
hasEnglishMT	boolean	Whether a machine-translated English version exists
citationString	string	Ready-to-use GB/T 7714 citation
matchedJournalTiers	array of strings	Journal tier(s) this result was filtered to, when a tier filter was applied
sourceUrl	string	Link to the paper's public metadata page
abstract	string	Full abstract (Author Profiles enrichment or paper detail lookups)
keywords	array of strings	Author-supplied keywords
doi	string	DOI, when CNKI lists one
institutions	array of strings	Author institutional affiliations (with Author Profiles enabled)

💰 Pricing

CNKI Scraper runs on pay per event pricing. You pay for the paper records you actually receive and, in citation-tracking mode, for each saved paper re-checked. Empty runs and failed requests cost nothing, and there is no subscription.

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🛠️ Tips

• Leave databaseTypes empty to search every CNKI database type at once, it does not mean zero results.
• Combine journalTiers with a keyword search to find only core-ranked work on a topic, useful for literature reviews that need to prioritize quality over volume.
• Turn on includeAuthorProfiles only when you need institution data. It fetches one extra page per result, so keep maxResults modest when you enable it.
• For a recurring "what's new on this topic" feed, schedule a run with onlyNewOrChanged turned on and a fixed stateName.

❓ FAQ

Does this actor download full-text articles or PDFs? No. Full-text and PDF content sits behind CNKI's own paid login and is out of scope for this actor. It returns bibliographic metadata: title, authors, abstract, keywords, DOI, journal, and citation data only.

Do I need a CNKI account or API key? No. Every field comes from CNKI's own publicly accessible metadata pages. No login, password, or API key is ever required.

Why is maxResults capped at 50? CNKI's own search interface only offers 10, 20, or 50 results per page, and this actor deliberately never requests a second page in a single search to keep every run fast and reliable. Run the actor again with a narrower filter (tier, database type, date range, or a different sort) to reach past the top 50 for a broad query.

How do I check whether a scholar's papers moved into a core-ranked journal? Save the scholar's papers from a search run, then run the actor again with trackCitationChanges on and that saved list in savedPapers. It reports back only the papers whose citation count actually moved.

Is this actor affiliated with CNKI (中国知网)? No. This actor is an independent tool that reads CNKI's own publicly accessible search and metadata pages. It is not built, endorsed, or operated by CNKI.

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