GNet Viewer

GNet Viewer analyzes domain connections and site relationships to reveal how pages and domains interlink, helping SEO teams map influence, identify central hubs, and surface opportunities for outreach and internal linking. It is designed for SEO professionals, web analysts, and growth teams who perform site audits, competitive benchmarking, and strategic planning. The tool accepts a domain and scope, derives a network model, and provides a concise summary of reach, authority paths, and topical clusters for decision making. Core Logic & Features: Build a directed graph from crawl and backlink data, compute centrality metrics (degree, betweenness, eigenvector) and clustering, identify hubs and clusters, and support depth control, subdomain inclusion, and multiple data sources. Required features include domain input, scope, depth; optional features include data source selection, filters, time window, and export options. The tool emphasizes reproducibility and explainability by providing raw graph data and derived metrics in standard formats. Inputs & Outputs: Inputs include domain string, depth integer 1-5, include_subdomains boolean, data_sources array, time_window string. Outputs include graph data consisting of nodes and edges, metrics table with centrality scores, hub rankings, and cluster IDs, top hubs list, and cluster summaries. Outputs can be serialized as JSON or CSV and consumed by downstream analytics. Algorithms & Calculations: Applies graph theory methods such as degree centrality (in_degree plus out_degree divided by n-1), betweenness centrality, eigenvector centrality, and clustering coefficient. Path-based reach estimates help identify navigation routes, and hub detection combines multiple signals to rank domains. All calculations are performed on the observed data and are limited by data quality and scope. Error & Edge Cases: Invalid domain or unresolved host returns an error; depth outside 1-5 is rejected; data_source unavailability yields partial results with transparent partials; rate limits, sampling bias, and inconsistent data require caution; non-ASCII domains are normalized. Industry/Region & Localization: Standards followed include RFC 3986 for domain naming and DNS semantics. Outputs use counts and ISO 8601 date formatting when applicable. Localization support includes locale-aware formatting for numbers and dates; no currency handling. Assumptions & Exclusions: Assumes data sources are public crawl and backlink indices; excludes private networks and paid links; not real-time; results may reflect sampling bias and update frequency; excludes sentiment and content quality analysis.