name: plumx-metrics-api
description: "Track research impact beyond citations via PlumX altmetrics API"
metadata:
openclaw:
emoji: "📊"
category: "literature"
subcategory: "metadata"
keywords: ["PlumX", "altmetrics", "research impact", "social media metrics", "usage statistics", "scholarly metrics"]
source: "https://plumanalytics.com/"
PlumX Metrics API
Overview
PlumX (by Elsevier/Plum Analytics) tracks 5 categories of research impact metrics beyond traditional citations: Usage, Captures, Mentions, Social Media, and Citations. It covers 130M+ research artifacts including articles, datasets, presentations, and videos. Available via Elsevier's API infrastructure. Requires an Elsevier API key.
Metric Categories
| Category | What it measures | Examples |
|---|
| Usage | Reading/viewing | Abstract views, PDF downloads, HTML views |
| Captures | Saving for later | Mendeley readers, CiteULike bookmarks |
| Mentions | Commentary | Blog posts, news articles, Wikipedia refs |
| Social Media | Sharing/discussion | Tweets, Facebook shares, Reddit posts |
| Citations | Formal references | Scopus, CrossRef, PubMed citations |
API Endpoints
Base URL
https://api.elsevier.com/analytics/plumx/
Get Metrics by DOI
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/doi/10.1038/nature14539"
Get Metrics by Other IDs
# By PubMed ID
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/pmid/25428114"
# By ISBN
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/isbn/9780262035613"
# By Scopus ID
curl -H "X-ELS-APIKey: $ELSEVIER_API_KEY" \
"https://api.elsevier.com/analytics/plumx/scopusId/84920765826"
Response Structure
{
"count_categories": [
{
"name": "capture",
"total": 15432,
"count_types": [
{"name": "READER_COUNT", "total": 15432, "sources": [
{"name": "Mendeley", "total": 15432}
]}
]
},
{
"name": "socialMedia",
"total": 3250,
"count_types": [
{"name": "TWEET_COUNT", "total": 2800},
{"name": "FACEBOOK_COUNT", "total": 450}
]
},
{
"name": "citation",
"total": 2100,
"count_types": [
{"name": "Scopus", "total": 1800},
{"name": "CrossRef", "total": 2100}
]
},
{
"name": "usage",
"total": 45000,
"count_types": [
{"name": "ABSTRACT_VIEWS", "total": 30000},
{"name": "LINK_OUTS", "total": 15000}
]
},
{
"name": "mention",
"total": 85,
"count_types": [
{"name": "NEWS_COUNT", "total": 45},
{"name": "BLOG_COUNT", "total": 25},
{"name": "WIKIPEDIA_COUNT", "total": 15}
]
}
]
}
Python Usage
import os
import requests
API_KEY = os.environ["ELSEVIER_API_KEY"]
BASE_URL = "https://api.elsevier.com/analytics/plumx"
HEADERS = {"X-ELS-APIKey": API_KEY, "Accept": "application/json"}
def get_plumx_metrics(doi: str) -> dict:
"""Get PlumX metrics for a paper by DOI."""
resp = requests.get(
f"{BASE_URL}/doi/{doi}",
headers=HEADERS,
)
resp.raise_for_status()
data = resp.json()
metrics = {}
for cat in data.get("count_categories", []):
category_name = cat["name"]
metrics[category_name] = {
"total": cat["total"],
"breakdown": {},
}
for ct in cat.get("count_types", []):
metrics[category_name]["breakdown"][ct["name"]] = ct["total"]
return metrics
def compare_impact(dois: list) -> list:
"""Compare PlumX metrics across multiple papers."""
results = []
for doi in dois:
metrics = get_plumx_metrics(doi)
results.append({
"doi": doi,
"citations": metrics.get("citation", {}).get("total", 0),
"captures": metrics.get("capture", {}).get("total", 0),
"social": metrics.get("socialMedia", {}).get("total", 0),
"usage": metrics.get("usage", {}).get("total", 0),
"mentions": metrics.get("mention", {}).get("total", 0),
})
return results
# Example: analyze a paper's multi-dimensional impact
metrics = get_plumx_metrics("10.1038/nature14539")
for category, data in metrics.items():
print(f"\n{category.upper()} (total: {data['total']})")
for metric_type, count in data["breakdown"].items():
print(f" {metric_type}: {count}")
# Example: compare two papers
# comparison = compare_impact([
# "10.1038/nature14539",
# "10.1126/science.aax2342",
# ])
PlumX vs Other Altmetric Services
| Feature | PlumX | Altmetric.com | Crossref Event Data |
|---|
| Metric categories | 5 comprehensive | Attention Score | Events only |
| Coverage | 130M+ artifacts | 30M+ outputs | DOI-based |
| Social media | Twitter, Facebook, Reddit | Twitter, Reddit, News | Twitter, Reddit, Wikipedia |
| Usage data | Yes (views, downloads) | No | No |
| Capture data | Yes (Mendeley readers) | Mendeley readers | No |
| Free access | Limited | Limited widget | Full API free |
References