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Upload 3 files
Browse files- OpenAlexEdges.R +101 -0
- OpenAlexEdgesDisp.R +85 -0
- OpenAlexNodes.R +85 -0
OpenAlexEdges.R
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authorPubEdges <- function(keywords,pub_start_date,pub_end_date){
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keywords <- keywords
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pub_start_date <- pub_start_date
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pub_end_date <- pub_end_date
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# create search engine function
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search_engine <- function(keywords,pub_start_date,pub_end_date){
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suppressPackageStartupMessages(library(openalexR))
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suppressPackageStartupMessages(library(tidyverse))
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options(openalexR.mailto = "[email protected]")
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# search engine
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works_search <- oa_fetch(
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entity = "works",
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title.search = keywords,
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cited_by_count = ">50",
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from_publication_date = pub_start_date,
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to_publication_date = pub_end_date,
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options = list(sort = "cited_by_count:desc"),
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verbose = FALSE
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)
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return(works_search)
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}
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# import nodes function
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source("openAlexNodes.R")
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# run author nodes function
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author_nodes <- authorPubNodes(keywords,pub_start_date,pub_end_date)
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# run search engine
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search_data <- search_engine(keywords,pub_start_date,pub_end_date)
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# grab authors and group them according to collaboration
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authors_collaboration_groups <- list()
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for (i in 1:nrow(search_data)){
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authors_collaboration_groups[[i]] <- search_data$author[[i]][2]
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}
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# grab all authors
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all_authors <- c()
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for (i in 1:length(authors_collaboration_groups)) {
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all_authors <- c(all_authors,authors_collaboration_groups[[i]][[1]])
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}
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# get length of each authors collaboration
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authors_length <- c()
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for(authors in 1:length(authors_collaboration_groups)){
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authors_length <- c(authors_length,authors_collaboration_groups[[authors]] |> nrow())
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}
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# grab all publications
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publications <- list()
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for (i in 1:nrow(search_data)){
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publications[[i]] <- rep(search_data$display_name[i], each = authors_length[i])
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}
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# place all publications in a vector
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all_publications <- c()
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for(i in 1:length(publications)){
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all_publications <- c(all_publications,publications[[i]])
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}
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# create author_to_publication data frame
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authors_to_publications <- data.frame(
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Authors = all_authors,
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Publications = all_publications
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)
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# create edges data frame
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author_publication_edges <- data.frame(
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Source = authors_to_publications$Authors,
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Target = authors_to_publications$Publications,
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Type = "directed",
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Weight = 1.0
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)
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# replace edges with id from nodes data set
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replace_edges_with_ids <- function(author_edges, author_nodes) {
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# Create a lookup table for node values to their corresponding Ids
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node_lookup <- setNames(author_nodes$Id, author_nodes$Node)
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# Use the lookup table to replace Source and Target values in author_edges
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author_edges$Source <- node_lookup[author_edges$Source]
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author_edges$Target <- node_lookup[author_edges$Target]
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return(author_edges)
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}
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# Call the function with your data frames
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author_publication_edges <- replace_edges_with_ids(author_publication_edges, author_nodes)
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return(author_publication_edges)
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}
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OpenAlexEdgesDisp.R
ADDED
@@ -0,0 +1,85 @@
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authorPubEdgesDisp <- function(keywords,pub_start_date,pub_end_date){
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keywords <- keywords
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pub_start_date <- pub_start_date
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pub_end_date <- pub_end_date
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# create search engine function
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search_engine <- function(keywords,pub_start_date,pub_end_date){
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suppressPackageStartupMessages(library(openalexR))
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suppressPackageStartupMessages(library(tidyverse))
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options(openalexR.mailto = "[email protected]")
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# search engine
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works_search <- oa_fetch(
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entity = "works",
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title.search = keywords,
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cited_by_count = ">50",
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from_publication_date = pub_start_date,
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to_publication_date = pub_end_date,
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options = list(sort = "cited_by_count:desc"),
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verbose = FALSE
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)
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return(works_search)
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}
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search_data <- search_engine(keywords,pub_start_date,pub_end_date)
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# grab authors and group them according to collaboration
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authors_collaboration_groups <- list()
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for (i in 1:nrow(search_data)){
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authors_collaboration_groups[[i]] <- search_data$author[[i]][2]
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}
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# grab all authors
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all_authors <- c()
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for (i in 1:length(authors_collaboration_groups)) {
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all_authors <- c(all_authors,authors_collaboration_groups[[i]][[1]])
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}
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# get length of each authors collaboration
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authors_length <- c()
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for(authors in 1:length(authors_collaboration_groups)){
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authors_length <- c(authors_length,authors_collaboration_groups[[authors]] |> nrow())
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}
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# grab all publications
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publications <- list()
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for (i in 1:nrow(search_data)){
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publications[[i]] <- rep(search_data$display_name[i], each = authors_length[i])
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}
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# place all publications in a vector
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all_publications <- c()
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for(i in 1:length(publications)){
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all_publications <- c(all_publications,publications[[i]])
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}
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# create author_to_publication data frame
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authors_to_publications <- data.frame(
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Authors = all_authors,
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Publications = all_publications
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)
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# create edges data frame
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author_publication_edges <- data.frame(
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Source = authors_to_publications$Authors,
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Target = authors_to_publications$Publications,
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Type = "directed",
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Weight = 1.0
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)
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return(author_publication_edges)
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}
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# author_edges <- authorPubEdgesDisp(keywords = c("information","analytics","management"),
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# pub_start_date = "2022-01-01",
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# pub_end_date = "2023-01-31")
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#
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# author_edges |> view()
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OpenAlexNodes.R
ADDED
@@ -0,0 +1,85 @@
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authorPubNodes <- function(keywords,pub_start_date,pub_end_date){
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keywords <- keywords
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pub_start_date <- pub_start_date
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pub_end_date <- pub_end_date
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# create search engine function
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search_engine <- function(keywords,pub_start_date,pub_end_date){
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suppressPackageStartupMessages(library(openalexR))
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suppressPackageStartupMessages(library(tidyverse))
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options(openalexR.mailto = "[email protected]")
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# search engine
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works_search <- oa_fetch(
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entity = "works",
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title.search = keywords,
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cited_by_count = ">50",
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from_publication_date = pub_start_date,
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to_publication_date = pub_end_date,
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options = list(sort = "cited_by_count:desc"),
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verbose = FALSE
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)
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return(works_search)
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}
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search_data <- search_engine(keywords,pub_start_date,pub_end_date)
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# grab authors and group them according to collaboration
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authors_collaboration_groups <- list()
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for (i in 1:nrow(search_data)){
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authors_collaboration_groups[[i]] <- search_data$author[[i]][2]
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}
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# grab all authors
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all_authors <- c()
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for (i in 1:length(authors_collaboration_groups)) {
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all_authors <- c(all_authors,authors_collaboration_groups[[i]][[1]])
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}
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# get length of each authors collaboration
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authors_length <- c()
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for(authors in 1:length(authors_collaboration_groups)){
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authors_length <- c(authors_length,authors_collaboration_groups[[authors]] |> nrow())
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}
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# grab all publications
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publications <- list()
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for (i in 1:nrow(search_data)){
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publications[[i]] <- rep(search_data$display_name[i], each = authors_length[i])
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}
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# place all publications in a vector
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all_publications <- c()
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for(i in 1:length(publications)){
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all_publications <- c(all_publications,publications[[i]])
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}
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# create author_to_publication data frame
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authors_to_publications <- data.frame(
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Authors = all_authors,
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Publications = all_publications
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)
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# stack the df so that authors and publications
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# are together as one column
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stacked_df <- stack(authors_to_publications)
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stacked_df <- unique.data.frame(stacked_df) # remove duplicate rows
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stacked_df <- stacked_df[-2] # delete second column in df
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# create author_publications_nodes df
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author_publication_nodes <- data.frame(
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Id = 1:nrow(stacked_df),
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Nodes = stacked_df$values,
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Label = stacked_df$values
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)
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return(author_publication_nodes)
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}
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