Google Scholar Citation Count Badge

WHAT IT DOES

This script scans Google Scholar search results and author profile pages for citation counts—total citations, h-index, i10-index, and citation counts per paper—and displays a floating badge panel showing summary statistics. It extracts citation metrics from the page, calculates total citations, average citations per paper, and identifies highly cited papers. A summary of the author's citation profile is displayed with color-coded indicators: green for high impact, yellow for medium, red for low. A one-click export function saves citation data as CSV or JSON. All citation snapshots are stored per domain locally for tracking over time.

WHERE IT RUNS

Works on Google Scholar search results pages (scholar.google.com) and author profile pages (scholar.google.com/citations). The script detects citation metrics using Google Scholar's page structure, including total citations, h-index, i10-index, and individual paper citations.

HOW TO USE

The panel appears automatically when you visit a Google Scholar profile or search results page. It detects citation metrics and displays summary stats: total citations, h-index, i10-index, and number of papers. The average citations per paper is shown below. A list of papers shows each paper's title, year, and citation count with color-coded impact indicators based on the average citation rate. Click "Refresh Data" to rescan for updated citation information. Export citation data as CSV for spreadsheet analysis or as JSON for programmatic use. Use "Clear History" to reset stored snapshots for the current domain. The panel automatically saves a snapshot each time you visit, building a history of citation metrics over time.

TECHNICAL MECHANISM: GOOGLE SCHOLAR CITATION EXTRACTION WITH METRIC CALCULATION AND IMPACT COLOR-CODING

The script uses a comprehensive detection strategy. First, it scans the page text for total citations using patterns like "Total citations: [number]," "Cited [number] times," and "Citation count: [number]." The h-index is extracted from patterns like "h-index: [number]" and "h: [number]." The i10-index is extracted from patterns like "i10-index: [number]." For paper entries, the script looks for Google Scholar paper containers (.gs_ai, .gs_r, .gsc_a_t, .gsc_a_tr, .gsc_a_td) and extracts the paper title from title elements, citation counts from "Cited by [number]" patterns, and publication year from year patterns. The script also scans text blocks for paper-like entries with citation counts as a fallback. The average citations per paper is calculated by summing citation counts and dividing by the number of papers. Impact color-coding uses the ratio of each paper's citations to the average: >2× average = high impact (green), >1× average = good impact (light green), >0.5× average = medium impact (yellow), ≤0.5× average = low impact (gray). Each snapshot stores the total citations, h-index, i10-index, total papers, average citations, and a list of papers with titles, citations, and years, capped at 30 entries per domain.

THE PANEL

The citation count badge appears in a draggable, resizable panel that remembers its position per site. The panel shows summary stats, average citations, a list of papers with impact color-coding, and history. Drag by the header to reposition, collapse to a compact icon with a click, and resize using the bottom-right corner. The panel snaps to screen edges for tidy placement and closes with the Escape key. All settings—panel position—persist per website using GM_setValue, so your view returns exactly as you left it.

PLEASE NOTE

This script requires the free BotGentz extension to run. The script relies on Google Scholar's current page structure—if Google Scholar updates their layout, citation detection may need updating. The script does not access your Google account credentials—all data is read from the visible page and processed locally. The citation count detection uses common patterns; some author profiles may use different formats. The impact color-coding is based on relative citation performance within the author's paper set. All data is stored locally in your browser via GM_setValue and never transmitted. The script is designed for tracking citation metrics, not for modifying or uploading data to Google Scholar.