fixed title and doi

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: ig.degree.betweenness
 Type: Package
-Title: Implementation of "Smith-Pittman" community detection algortihm with a gradient evident in social partitioning by Smith, Pittman and Xu (2024) for "igraph" objects 
+Title: Implementation of "Smith-Pittman" Community Detection Algortihm with a Gradient Evident in Social Partitioning by Smith, Pittman and Xu (2024) for "igraph" Objects
 Version: 0.1.0
 Authors@R: c(
     person(
@@ -31,7 +31,7 @@ Description: Implements the "Smith-Pittman" community detection algorithm
     networks, with a gradient evident in social partitioning. The package 
     provides functions for community detection, visualization, and analysis of 
     the resulting community structure. Methods are based on results from Smith, 
-    Pittman and Xu (2024) <https://doi.org/10.48550/arXiv.2411.01394>.
+    Pittman and Xu (2024) <doi:10.48550/arXiv.2411.01394>.
 License: MIT + file LICENSE
 URL: https://github.com/benyamindsmith/ig.degree.betweenness
 BugReports: https://github.com/benyamindsmith/ig.degree.betweenness/issues

R/cluster_degree_betweenness.R

@@ -22,7 +22,7 @@
 #' @importFrom igraph components
 #' @importFrom rlist list.append
 #' @import igraphdata
-#' @references Smith et al (2024) "Centrality in Collaboration: A Novel Algorithm for Social Partitioning Gradients in Community Detection for Multiple Oncology Clinical Trial Enrollments", <https://doi.org/10.48550/arXiv.2411.01394>
+#' @references Smith et al (2024) "Centrality in Collaboration: A Novel Algorithm for Social Partitioning Gradients in Community Detection for Multiple Oncology Clinical Trial Enrollments", <doi:10.48550/arXiv.2411.01394>
 #' @export
 #' @examples
 #' library(igraphdata)