Scholar Metrics Analysis

This page collects examples for paper citation counts, researcher-level Semantic Scholar metrics, and journal impact factors.

Paper Citation Counts

Fetch citation counts by DOI using Semantic Scholar:

>>> from paperscraper.citations import get_citations_by_doi
>>> get_citations_by_doi("10.1021/acs.jcim.3c00132")
12  # Semantic Scholar citation count.

You can also query Google Scholar by title:

>>> from paperscraper.citations import get_citations_from_title
>>> title = "GT4SD: Generative Toolkit for Scientific Discovery"
>>> get_citations_from_title(title)
9  # Google Scholar citation count.

Citation counts can differ between Semantic Scholar and Google Scholar. Google Scholar queries may trigger captchas during automated use. Semantic Scholar throughput can be increased with SS_API_KEY:

export SS_API_KEY=YOUR_API_KEY

For larger author-level runs, SS_REQUEST_TIMEOUT, SS_CONCURRENCY_LIMIT, and SS_RATE_LIMIT_DELAY can be tuned through environment variables.

Researcher Metrics

Semantic Scholar author pages expose paperCount, citationCount, and hIndex. You can query them by Semantic Scholar Author ID:

from paperscraper.citations.utils import semantic_scholar_requests_get

ssaid = "2062641025"
metrics = semantic_scholar_requests_get(
    f"https://api.semanticscholar.org/graph/v1/author/{ssaid}",
    params={"fields": "name,paperCount,citationCount,hIndex"},
).json()

{
    "authorId": "2062641025",
    "name": "Jannis Born",
    "paperCount": 63,
    "citationCount": 1910,
    "hIndex": 21,
}

Resolve the same author by name:

>>> from paperscraper.citations.utils import author_name_to_ssaid
>>> author_name_to_ssaid("Jannis Born")
("2062641025", "Jannis Born")

Or resolve through ORCID first:

>>> from paperscraper.citations.orcid import orcid_to_author_name
>>> from paperscraper.citations.utils import author_name_to_ssaid
>>> name = orcid_to_author_name("0000-0001-8307-5670")
>>> author_name_to_ssaid(name)
("2062641025", "Jannis Born")

If you need the actual Semantic Scholar paper IDs for an author, use get_papers_for_author:

>>> from paperscraper.citations.utils import get_papers_for_author
>>> paper_ids = get_papers_for_author("2062641025")
>>> len(paper_ids)
63  # Number of papers linked to this Semantic Scholar author record.
>>> paper_ids[0]
'6c245545fcb88df49cf921ba0871b40818665b92'

Citation and paper counts can change as Semantic Scholar updates author records.

Journal Impact Factors

Use Impactor to search journal names, abbreviations, E-ISSNs, or NLM IDs.

>>> from paperscraper.impact import Impactor
>>> impactor = Impactor()
>>> impactor.search("Nat Comms", threshold=85, sort_by="impact")
[
    {"journal": "Nature Computational Science", "factor": 18.3, "score": 88},
    {"journal": "Nature Communications", "factor": 15.7, "score": 94},
    {"journal": "Natural Computing", "factor": 1.6, "score": 88},
]

threshold defaults to 100, which behaves like an exact search. Lower values allow fuzzier matches. sort_by can be "impact", "journal", or "score".

Search by abbreviation, NLM ID, or E-ISSN:

>>> impactor.search("Nat Rev Earth Environ")
[{"journal": "Nature Reviews Earth & Environment", "factor": 71.5, "score": 100}]
>>> impactor.search("101771060")
[{"journal": "Nature Reviews Earth & Environment", "factor": 71.5, "score": 100}]
>>> impactor.search("2662-138X")
[{"journal": "Nature Reviews Earth & Environment", "factor": 71.5, "score": 100}]

Filter by impact factor range:

>>> impactor.search("Neural network", threshold=85, min_impact=1.5, max_impact=20)
[
    {"journal": "IEEE Transactions on Neural Networks and Learning Systems", "factor": 8.9, "score": 93},
    {"journal": "NEURAL NETWORKS", "factor": 6.3, "score": 91},
    {"journal": "Network", "factor": 3.1, "score": 92},
    {"journal": "NETWORK-COMPUTATION IN NEURAL SYSTEMS", "factor": 1.6, "score": 92},
    {"journal": "WORK-A Journal of Prevention Assessment & Rehabilitation", "factor": 1.5, "score": 86},
]

Return all available fields:

>>> impactor.search("quantum information", threshold=90, return_all=True)
[
    {
        "factor": 8.3,
        "jcr": "Q1",
        "nlm_id": "101722857",
        "journal": "npj Quantum Information",
        "issn": ".",
        "zky": ".",
        "journal_abbr": "npj Quantum Inf",
        "eissn": "2056-6387",
        "score": 92,
    },
    {
        "factor": 2.9,
        "jcr": "Q2",
        "nlm_id": "101703749",
        "journal": "Information",
        "issn": ".",
        "zky": ".",
        "journal_abbr": "Information (Basel)",
        "eissn": "2078-2489",
        "score": 95,
    },
    {
        "factor": 1.3,
        "jcr": "Q2",
        "nlm_id": "9877123",
        "journal": "NATION",
        "issn": "0027-8378",
        "zky": ".",
        "journal_abbr": "Nation",
        "eissn": "0027-8378",
        "score": 91,
    },
    {
        "factor": 1.1,
        "jcr": ".",
        "nlm_id": "138060",
        "journal": "Reformation",
        "issn": "1357-4175",
        "zky": ".",
        "journal_abbr": "Reformation",
        "eissn": "1752-0738",
        "score": 90,
    },
]