R — Link Explorer |verified|

Unlock the Power of Your Data with R Link Explorer

1. tidyverse: For cleaning and organizing the raw CSV data.
2. igraph: The engine that calculates the network mathematics (clusters, distances, degrees).
3. visNetwork: The library that creates the interactive HTML widget (the actual visual explorer).
4. Shiny: (Optional) For wrapping the visualization in a user-friendly web application.

Technical approach

• Use parsers: roxygen2, pkgload, xml2, commonmark, and custom regex for extracting references.
• Build graph using igraph or tidygraph; visualize with visNetwork, ggraph, or a JavaScript frontend (D3, Cytoscape.js).
• Use parallel crawling with error handling, rate limiting, and link canonicalization.
• Leverage git for timeline diffs and to locate source of changes.
• Provide R package (rlinkexplorer) with functions: crawl_project(), build_graph(), analyze_graph(), visualize_graph(), check_links(), report_html().

• Filter by "Lost": Toggle to "Lost only" to see who removed you.
• Filter by "Nofollow": Identify how many links have the rel="nofollow" tag. A healthy profile has 30-50% nofollow.
• Filter by "Follow": These are the "link juice" passing links. Prioritize these.

2. Advanced 3D Mapping & Live Traffic R-Link Explorer comes pre-loaded with high-resolution 3D maps from leading providers like TomTom. But static maps are a thing of the past. Thanks to live traffic updates (via your smartphone or built-in connected services), the system dynamically recalculates your route to avoid jams, roadworks, and accidents. Estimated arrival times become genuinely reliable. r link explorer