push new website and new functions

DESCRIPTION

@@ -1,31 +1,23 @@
 Package: networkflow
 Title: Functions For A Workflow To Manipulate Networks
-Version: 0.1.0
+Version: 1.0.0
 Date: 2022-11-25
 Authors@R: c(
     person("Aurélien", "Goutsmedt", , "agoutsmedt@gmail.com", role = c("cre", "aut"),
            comment = c(ORCID = "0000-0002-3788-7237")),
     person("Alexandre", "Truc", , "alexandre.truc77@gmail.com", role = c("aut"),
-           comment = c(ORCID = "0000-0002-1328-7819"))
+           comment = c(ORCID = "0000-0002-1328-7819")),
+    person("Thomas", "Delcey", role = c("aut"), comment = c(ORCID = "0000-0003-0546-1474"))
   )
-Author: Aurélien Goutsmedt and Alexandre Truc.
+Author: Aurelien Goutsmedt, Alexandre Truc and Thomas Delcey.
 Maintainer: Aurélien Goutsmedt <agoutsmedt@hotmail.fr>
-Description: This package proposes a series of function to make it easier
-    and quicker to work on networks. It mainly targets working on
-    bibliometric networks (see the
-    [biblionetwork](https://github.com/agoutsmedt/biblionetwork) package
-    for creating such networks). This package heavily relies on
-    [igraph](https://igraph.org/r/) and
-    [tidygraph](https://tidygraph.data-imaginist.com/index.html), and aims
-    at producing ready-made networks for projecting them using
-    [ggraph](https://ggraph.data-imaginist.com/). This package does not
-    invent nothing new, properly speaking, but it allows the users to
-    follow more quickly and easily the main steps of network manipulation,
-    from creating the graph to projecting it. It is inspired by what could
-    be done with [GEPHI](https://gephi.org/): the package allows the use
-    of the Leiden community detection algorithm, as well as of the Force
-    Atlas 2 layout, both being unavailable in igraph (and so in
-    tidygraph).
+Description: Provides a workflow to build, analyze, and visualize projected
+    networks from tabular data. The package supports dynamic analysis across
+    time windows, including cluster detection and cross-period cluster matching.
+    It also covers network construction, interpretation, static plotting, and
+    interactive exploration through a 'shiny' app. Although designed for
+    projected networks (e.g., article -> reference), it can be used more
+    generally with 'tbl_graph' objects.
 License: MIT + file LICENSE
 URL: https://github.com/agoutsmedt/networkflow,
     https://agoutsmedt.github.io/networkflow/
@@ -71,6 +63,4 @@ Remotes:
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
-
-
+RoxygenNote: 7.3.3

NAMESPACE

@@ -4,7 +4,6 @@ export("%>%")
 export(add_clusters)
 export(add_node_roles)
 export(build_dynamic_networks)
-export(build_dynamic_networks2)
 export(build_network)
 export(color_alluvial)
 export(color_networks)

NEWS.md

@@ -1,4 +1,6 @@
-# networkflow 0.1.0 (Development)
+# networkflow 1.0.0
+
+First stable release.
 
 Deprecated and new functions:
 

R/Authors_stagflation.R

@@ -4,11 +4,11 @@
 #' the US stagflation and their authors (`Nodes_stagflation` just takes the first author;
 #' here is the complete list of authors per document).
 #'
-#' @format A data frame with 558 rows and 7 variables:
+#' @format A data frame with 231 rows and 3 variables:
 #' \describe{
-#'   \item{ItemID_Ref}{Identifier of the document published by the author}
-#'   \item{Author}{Author of the document}
-#'   \item{Order}{Use this as a label for nodes}
+#'   \item{source_id}{Identifier of the document published by the author}
+#'   \item{author_name}{Author of the document}
+#'   \item{author_order}{Author order in the document author list}
 #' }
 #' @source Goutsmedt A. (2020) “From Stagflation to the Great Inflation: Explaining the 1970s US Economic
 #' Situation”. Revue d’Economie Politique, Forthcoming 2021.

R/Edges_coupling.R

@@ -1,10 +1,10 @@
 #' Edges For Bibliographic Coupling Network Of Articles and Books Explaining the 1970s US Stagflation.
 #'
 #' A dataset containing the edges of the bibliographic coupling network of articles and books on stagflation.
-#' Built by using [Ref_stagflation]: `biblionetwork::biblio_coupling(Ref_stagflation,"Citing_ItemID_Ref","ItemID_Ref")`.
+#' Built by using [Ref_stagflation]: `biblionetwork::biblio_coupling(Ref_stagflation,"source_id","target_id")`.
 #' Could be used with [Nodes_coupling] to create a network with tidygraph.
 #'
-#' @format A data frame with 154 rows and 6 variables:
+#' @format A data frame with 2593 rows and 5 variables:
 #' \describe{
 #'   \item{from}{Identifier of the Source document on stagflation, in character format}
 #'   \item{to}{Identifier of the Target document on stagflation, in character format}

R/Nodes_coupling.R

@@ -7,12 +7,12 @@
 #'
 #' @format A data frame with 154 rows and 6 variables:
 #' \describe{
-#'   \item{ItemID_Ref}{Identifier of the document on stagflation, in character format}
-#'   \item{Author}{Author of the document on stagflation}
-#'   \item{Author_date}{Use this as a label for nodes}
-#'   \item{Year}{Year of publication of the document}
-#'   \item{Title}{Title of the document}
-#'   \item{Journal}{Journal of publication of the document (if an article)}
+#'   \item{source_id}{Identifier of the document on stagflation, in character format}
+#'   \item{source_author}{Author of the document on stagflation}
+#'   \item{source_label}{Use this as a label for nodes}
+#'   \item{source_year}{Year of publication of the document}
+#'   \item{source_title}{Title of the document}
+#'   \item{source_journal}{Journal of publication of the document (if an article)}
 #' }
 #' @source Created from `Nodes_stagflation.rda`
 

R/Nodes_stagflation.R

@@ -4,15 +4,15 @@
 #' what happened in the US economy in the 1970s, as well as all the articles and books
 #' cited at least twice by the first set of articles and books (on the stagflation).
 #'
-#' @format A data frame with 558 rows and 7 variables:
+#' @format A data frame with 654 rows and 7 variables:
 #' \describe{
-#'   \item{ItemID_Ref}{Identifier of the document}
-#'   \item{Author}{Author of the document}
-#'   \item{Author_date}{Use this as a label for nodes}
-#'   \item{Year}{Year of publication of the document}
-#'   \item{Title}{Title of the document}
-#'   \item{Journal}{Journal of publication of the document (if an article)}
-#'   \item{Type}{If "Stagflation", the document is listed as an explanation of the US stagflation.
+#'   \item{source_id}{Identifier of the document}
+#'   \item{source_author}{Author of the document}
+#'   \item{source_label}{Use this as a label for nodes}
+#'   \item{source_year}{Year of publication of the document}
+#'   \item{source_title}{Title of the document}
+#'   \item{source_journal}{Journal of publication of the document (if an article)}
+#'   \item{source_type}{If "Stagflation", the document is listed as an explanation of the US stagflation.
 #'   If "Non-Stagflation", the document is cited by a document explaining the stagflation}
 #' }
 #' @source Goutsmedt A. (2020) “From Stagflation to the Great Inflation: Explaining the 1970s US Economic

R/Ref_stagflation.R

@@ -6,12 +6,12 @@
 #'
 #' @format A data frame with 4416 rows and 6 variables:
 #' \describe{
-#'   \item{Citing_ItemID_Ref}{Identifier of the citing document}
-#'   \item{ItemID_Ref}{Identifier of the cited document}
-#'   \item{Author}{Author of the cited document}
-#'   \item{Year}{Year of publication of the cited document}
-#'   \item{Title}{Title of the cited document}
-#'   \item{Journal}{Journal of publication of the cited document (if an article)}
+#'   \item{source_id}{Identifier of the citing document}
+#'   \item{target_id}{Identifier of the cited document}
+#'   \item{target_author}{Author of the cited document}
+#'   \item{target_year}{Year of publication of the cited document}
+#'   \item{target_title}{Title of the cited document}
+#'   \item{target_journal}{Journal of publication of the cited document (if an article)}
 #' }
 #' @source Goutsmedt A. (2020) “From Stagflation to the Great Inflation: Explaining the 1970s US Economic
 #' Situation”. Revue d’Economie Politique, Forthcoming 2021.