Apply intuitive visualization layouts on undirected/directed graphs, based on prominence
diff --git a/manual/gui/index.html b/manual/gui/index.html
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Viewing or Plotting the Adjace
Using Known Datasets
-
SocNetV can recreate well-known datasets. See Recreating Famous Datasets.
+
SocNetV can recreate well-known datasets. See Recreating Famous Datasets.
Random Network Creation
-
SocNetV can generate random networks based on various models. See Network Generation.
+
SocNetV can generate random networks based on various models. See Network Generation.
Web Crawler
-
SocNetV includes a web crawler to analyze networks of web pages. See Web Crawler Documentation.
+
SocNetV includes a web crawler to analyze networks of web pages. See Web Crawler Documentation.
Printing and Exporting
To print:
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@@ -126,7 +126,7 @@
Features of SocNetV
Barabási–Albert Scale-Free
Erdős–Rényi
Watts-Strogatz Small-World
-See more in the Random Networks section.
+See more in the
Random Networks section.
@@ -137,7 +137,7 @@ Features of SocNetV
Diameter
Geodesic distances
Clustering coefficient
-See details in the Cohesion Metrics section.
+See details in the
Cohesion Metrics section.
@@ -148,7 +148,7 @@ Features of SocNetV
Eigenvector centrality
Closeness centrality
PageRank prestige
-Explore these metrics in the Centralities section.
+Explore these metrics in the
Centralities section.
@@ -157,13 +157,13 @@ Features of SocNetV
Structural Equivalence Analysis
Perform hierarchical clustering, actor similarity, and tie profile dissimilarity analysis.
-See more in Structural Equivalence.
+See more in Structural Equivalence.
Visualization Models
@@ -173,7 +173,7 @@
Features of SocNetV
Level-based
Nodal sizes by centrality score
Force-directed placement (Kamada-Kawai, Fruchterman-Reingold)
-Learn more in the Visualization section.
+Learn more in the
Visualization section.
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