Start small. Pull a few backlinks from Moz or Majestic. Then, gradually build your own link scoring system. Before you know it, you’ll have a custom, automated, and infinitely flexible link analysis suite—all inside R.
For those working specifically with network data, R offers dedicated tools for extracting and analyzing link communities. The package is a powerful solution for extracting link communities from networks of arbitrary size and type. Whether your network is directed, weighted, both, or neither, linkcomm can handle it. The package is particularly valuable for researchers who need to make sense of complex data sets by identifying cohesive groups of links that share common nodes.
What are you trying to accomplish with R-Link Explorer (e.g., map updates, custom POIs, backups)? What Renault vehicle model and year do you own? r link explorer
library(httr) library(jsonlite) response <- GET("https://api.ahrefs.com/v3/site-explorer/backlinks", query = list(target = "example.com", token = "your_token")) data <- fromJSON(content(response, "text"))
For detecting coordinated behavior, the package identifies coordinated link sharing behavior (CLSB) across sets of URLs, outputting networks of entities that performed such coordinated actions. This can be invaluable for social media analysis, misinformation research, and understanding information cascades. Start small
# Function to explore a URL explore_url <- function(url) # Check if URL is valid if (is_url(url)) # You can add more functionality here, like opening the URL, extracting content, etc. cat("Valid URL: ", url, "\n") else cat("Invalid URL: ", url, "\n")
When users click a map marker, the corresponding table row highlights. Click that same table row, and the map zooms and shows a popup. This bidirectional behavior creates a fluid, intuitive user experience. Before you know it, you’ll have a custom,
If you are asking because you are having trouble with it, here are common "features" users often inquire about:
Place your vehicle's official R-Link SD card into your computer's built-in card reader or an external USB adapter. How to Use R-Link Explorer to Manage Your System
Using typically involves generating a graph, extracting link communities, and visualizing the results through various layout options, such as the Spencer circle layout. It allows for the calculation of centrality measures specific to link communities and the discovery of nested communities.
Drag and drop .ov2 (points of interest) and .bmp (associated icons) files directly into this map folder using the R-Link Explorer interface.