🤖 AI Summary
This study addresses the limitations of existing academic platforms in providing fine-grained author metadata and geographic visualization, which are either unavailable or prohibitively costly. The authors propose an automated analytical framework that leverages a single Google Scholar user ID and integrates data from five sources—Google Scholar, OpenAlex, CrossRef, Semantic Scholar, and OpenStreetMap—through a five-stage pipeline for paper parsing, author disambiguation, and geocoding. Key innovations include a Unicode-resilient metadata parser, a two-stage institutional similarity–based disambiguation mechanism, and a city-level location repair method using OpenAlex. The system increases city-level geographic coverage for authors from 0% to approximately 60%, reduces h-index attribution errors by up to ninefold, and produces interactive HTML maps alongside structured analytical reports.
📝 Abstract
Understanding the geographic reach and community structure of one's scholarly citations is increasingly valuable for career development, grant applications, and collaboration discovery -- yet accessible tools for answering these questions remain scarce. Existing bibliometric platforms either require costly institutional subscriptions or expose only aggregate citation counts without granular per-author metadata. We present CiteRadar, an open-source system that accepts a single Google Scholar user identifier and automatically produces a structured output folder containing: the author's complete publication list, all retrieved citing papers with enriched author metadata, two ranked author tables (by citation frequency and by h-index), a plain-text statistical summary, and a self-contained interactive HTML world map -- all from a single command-line invocation. CiteRadar integrates five heterogeneous data sources -- Google Scholar, OpenAlex, CrossRef, Semantic Scholar, and OpenStreetMap Nominatim -- through a carefully engineered five-stage pipeline. Key technical contributions include: (1) a Scholar meta-string parser resilient to Unicode non-breaking-space separators, a pervasive but undocumented quirk in Scholar's HTML that silently corrupts venue and year fields when unhandled; (2) a two-stage author disambiguation system using stop-word-filtered institution name similarity to guard against the well-known same-name entity-merging failure mode in bibliometric databases, demonstrated to eliminate h-index attribution errors of up to 9x the correct value; (3) an OpenAlex web-URL to API-URL conversion fix that raises the fraction of author records with city-level location data from 0% to ~60%; and (4) a logarithmically-scaled interactive Folium world map with per-city researcher popups, rendered as a fully self-contained HTML file.