| Title: | Cognitive Mapping Tools Based on Coding of Textual Sources |
| Version: | 0.9.3 |
| Date: | 2021-12-22 |
| Description: | Functions for building cognitive maps based on qualitative data. Inputs are textual sources (articles, transcription of qualitative interviews of agents,...). These sources have been coded using relations and are linked to (i) a table describing the variables (or concepts) used for the coding and (ii) a table describing the sources (typology of agents, ...). Main outputs are Individual Cognitive Maps (ICM), Social Cognitive Maps (all sources or group of sources) and a list of quotes linked to relations. This package is linked to the work done during the PhD of Frederic M. Vanwindekens (CRA-W / UCL) hold the 13 of May 2014 at University of Louvain in collaboration with the Walloon Agricultural Research Centre (project MIMOSA, MOERMAN fund). |
| URL: | https://frdvnw.gitlab.io/cogmapr/ |
| BugReports: | https://gitlab.com/FrdVnW/cogmapr/-/issues |
| License: | GPL-3 |
| SystemRequirements: | libcurl: libcurl-devel (rpm) or libcurl4-openssl-dev (deb). |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.1 |
| Imports: | grDevices, methods, utils, grid, graph, Rgraphviz, ggplot2, magrittr, dplyr (≥ 0.8.0.1), tidyr |
| biocViews: | graph, Rgraphviz |
| Suggests: | testthat, car |
| Maintainer: | Frédéric M. Vanwindekens <f.vanwindekens@cra.wallonie.be> |
| NeedsCompilation: | no |
| Packaged: | 2022-01-04 14:39:22 UTC; fred |
| Author: | Frédéric M. Vanwindekens
 [aut, cre],
Didier Stilmant [aut, ths],
Philippe V. Baret [aut, ths] |
| Repository: | CRAN |
| Date/Publication: | 2022-01-04 15:40:07 UTC |
cogmapr: Cognitive Mapping Tools Based on Coding of Textual Sources
Description
Functions for building cognitive maps based on qualitative data. Inputs are textual sources (articles, transcription of qualitative interviews of agents,...). These sources have been coded using relations and are linked to (i) a table describing the variables (or concepts) used for the coding and (ii) a table describing the sources (typology of agents, ...). Main outputs are Individual Cognitive Maps (ICM), Social Cognitive Maps (all sources or group of sources) and a list of quotes linked to relations. This package is linked to the work done during the PhD of Frederic M. Vanwindekens (CRA-W / UCL) hold the 13 of May 2014 at University of Louvain in collaboration with the Walloon Agricultural Research Centre (project MIMOSA, MOERMAN fund).
Author(s)
Maintainer: Frédéric M. Vanwindekens f.vanwindekens@cra.wallonie.be (ORCID)
Authors:
Didier Stilmant d.stimant@cra.wallonie.be [thesis advisor]
Philippe V. Baret philippe.baret@uclouvain.be [thesis advisor]
See Also
Useful links:
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Centralities of concepts
Description
Compute the centrality of concepts
Usage
ConceptCentrality(project, filters = NULL, units = "all", weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Compute the centrality of concepts
Value
A data frame with the value of the centrality (n) of vertices.
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptCentrality(my.project)
Centrality of vertices by document
Description
Centrality of vertices by document
Usage
ConceptCentralityIndiv(project, min.weight = 1, weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Centrality of vertices by document
Value
A data frame of Centrality by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptCentralityIndiv(my.project)
Indegrees of concepts
Description
Compute the indegree of concepts
Usage
ConceptIndegree(project, filters = NULL, units = "all", weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Compute the indegree of concepts
Value
A data frame with the value of the indegree (n) of vertices.
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptIndegree(my.project)
Indegree of vertices by document
Description
Indegree of vertices by document
Usage
ConceptIndegreeIndiv(project, min.weight = 1, weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Indegree of vertices by document
Value
A data frame of Indegree by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptIndegreeIndiv(my.project)
Concept Indicators of vertices by document
Description
Concept Indicators of vertices by document
Usage
ConceptIndicIndiv(project, min.weight = 1, weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Concept Indicators of vertices by document
Value
A data frame of Concept Indicators by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptIndicIndiv(my.project)
Summary table on concept comparisons by indicator
Description
Summary table on concept comparisons by indicator
Usage
ConceptIndicSummary(project, units)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
Details
This function produce a summary table based on concept comparisons by indicator.
Value
A data frame
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
## More documents are needed for running this function
## ConceptIndicSummary(my.project, units = c("Belgium", "Québec"))
Concepts indicators of a Social Cognitive Map
Description
Compute the indicators of concepts of a Social Cognitive Map
Usage
ConceptIndicators(project, filters = NULL, units = "all", weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Compute the indicators of concepts of a Social Cognitive Map (centrality, indegree, outdegree). It build a user friendly data frame. It includes the 'receiver' and the transmitter character of each vetex. The receiver character of a concept is calculated as the part of the indegree of this concept on its centrality. The transmitter character of a concept is calculated as the part of the outdegree of this concept on its centrality.
(add formulae)
Value
A data frame with the value of some indicators linked to vertices of a map.
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptIndicators(my.project)
Concept Indicators of vertices by document (tidy data)
Description
Concept Indicators of vertices by document (tidy data)
Usage
ConceptIndicatorsICM(project, doc_id = "all")
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
doc_id |
"all" (default) or the ID of document to include. |
Details
Concept Indicators of vertices by document (tidy data)
Value
A data frame (tidy data) with all indicators, their values by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptIndicatorsICM(my.project)
ConceptIndicatorsICM(my.project, 2)
Compute the outdegree of concepts
Description
Compute the outdegree of concepts##' @title Outdegrees of concepts
Usage
ConceptOutdegree(project, filters = NULL, units = "all", weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Value
A data frame with the value of the outdegree (n) of vertices.
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptOutdegree(my.project)
Outdegree of vertices by document
Description
Outdegree of vertices by document
Usage
ConceptOutdegreeIndiv(project, min.weight = 1, weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Outdegree of vertices by document
Value
A data frame of Outdegree by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ConceptOutdegreeIndiv(my.project)
Compare value of concepts indicators between maps
Description
This function test the differences between the properties of concepts
Usage
ConceptTest(project, units, output = "p.value", sep = ">", coder = "qcoder")
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
The units to compare |
output |
"p.value" (default) or "raw.data". |
sep |
Separation used in the relationships definition. Default is ">" (ex : 1>3) |
coder |
Coding tool used for this project. Default is "qcoder" (only implemented now) |
Details
This function test the differences between the properties of concepts (indegree, outdegree, centrality) between groups of documents (i.e. between social cognitive maps). Till now, only two excluding groups can be tested (ex. document from one country vs another country, from a group of players vs another group of players). It is not possible to compare non exclusive groups (ex. map from one country vs map from one group of players, as some documents can be in the two groups!). For this test, the 'wilcoxon.test' is done. If output = 'p.value', the function returns the results of the tests, one test for each concepts of the map. If output = 'raw.data', the function returns the raw data on which the tests are done, one data frame by concept. This option can be used to export data and perform other statistical tests.
Value
A data frame (if output = "p.value"), a list of data frame (if output = "raw.data").
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
## need more documents
ConceptTest(my.project, units = c("Belgium", "Québec"))
Summary table on concept comparisons
Description
Summary table on concept comparisons
Usage
ConceptTestSummary(project, units, limit.p.value = 0.05)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
The units to compare |
limit.p.value |
A numeric. |
Details
This function produce a summary table based on concept comparisons and is reactive to a limit of p.value beyond which differences are considered as significant and are reported in the table
Value
A data frame
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
## More documents are needed for running this function
## ConceptTestSummary(my.project, units = c("Belgium", "Québec"), 0.6)
Extract all edges from a Qualitative Data Analysis project
Description
This function opens a Qualitative Data Analysis (QDA) project and extracts edge information.
Usage
EdgCMap(project, sep = ">", coder = "qcoder")
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
sep |
(==Depreciated, with RQDA project==) A character string (often a single character) that is used in RQDA in order to express the relationships between two variables. Default is "_" if codes used in RQDA are of the form : "x_y" (i.e. relationship from x to y), but it is possible to use ">", "->", "–>" or even "—>" |
coder |
A character string indicating the coding tool used for coding the QDA. The only tool supported now is 'qcoder'. Earlier version of cogmapr worked with "RQDA" project (no more maintened). |
Details
The coding used in the QDA have to be done using the 'cogamp-dev' branch of the qcoder package (github : 'FrdVnW/qcoder'). devtools::install_github('FrdVnW/qcoder', ref = "cogmap-dev", upgrade = 'never')
Value
A data.frame with the relationships identified in the interviews. Each relationships ('coding_id') is linked to an agent ('doc_ed'), an edge's name ('edge'), the varible at the origin of the relationships ('concept_from'), the variable at the end of the relationships ('concept_to'), other properties of the relationships ('coding_sign', 'coding_weight', 'coding_class' and 'document_part') and the quotes linked to relationships ('selected_text').
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
EdgCMap(my.project)
Extract all edges from a Qualitative Data Analysis project for individual cognitive mapping
Description
This function opens a Qualitative Data Analysis (QDA) project and extracts edge information for individual cognitive mapping
Usage
EdgIndCMap(project, min.weight = 1, weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
The coding used in the QDA have to be done using the 'cogamp-dev' branch of the qcoder package (github : 'FrdVnW/qcoder'). devtools::install_github('FrdVnW/qcoder', ref = "cogmap-dev", upgrade = 'never')
Value
A data.frame
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
EdgIndCMap(my.project)
Aggregation of the relationships identified in a serie of Individual Cognitive Maps
Description
This function will produce a data frame that contains all relationships of a serie of Individual Cognitive Maps. The weights of these relationships are calculated.
Usage
EdgSocCMap(
project,
min.weight = 1,
filters = NULL,
units = "all",
weighted.icm = FALSE
)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
The function can be used to produce a data frame that contains only the relation with a minimum weight or that concerns only a type of agents.
Value
A data frame with four or five variables : ##'
- $edge
The name of the relationship, of the generic form x~y
- $FACTOR
If used, the factor the parameter variable]. This variable contains then the levels of the factor defined in the parameter group used as subset criteria
- $weight
The weight of each relationship
- $from
The number of the vertex at the origin of the relationship
- $to
The number of the vertex at the end of the relationship
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
EdgSocCMap(my.project)
EdgSocCMap(my.project)
EdgSocCMap(my.project, min.weight=3)
EdgSocCMap(my.project, min.weight=6, weighted.icm=TRUE)
Graph indicators of a social cognitive map
Description
Compute the graph indicators of a Social Cognitive Map (at graph level)
Usage
GraphIndicators(project, filters = NULL, units = "all", weighted.icm = FALSE)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
Details
Compute some indicators from the graph theory and applies them to a Social Cognitive Map :
dimension : the number of vertices
n_transmitter : the number of transmitter vertices
n_receiver : the number of receiver vertices
n_ordinary : the number of ordinary vertices (transmitter & receiver)
connections : the number of edges
density : ...
complexity_a : ....
complexity_b : ...
hierarchy : ...
(== add formulae ==)
Source : Oezesmi & Oezesmi, 2004
Value
A data frame with the value of some indicators linked to the map
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
GraphIndicators(my.project)
GraphIndicators(my.project, units = "Belgium")
GraphIndicators(my.project, units = "Québec")
Graph Indicators of vertices by document (tidy data)
Description
Graph Indicators of vertices by document (tidy data)
Usage
GraphIndicatorsICM(project, doc_id = "all")
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
doc_id |
"all" (default) or the ID of document to include. |
Details
Graph Indicators of vertices by document (tidy data)
Value
A data frame (tidy data) with all indicators, their values by document (ICM)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
GraphIndicatorsICM(my.project)
GraphIndicatorsICM(my.project, 2)
Table of graph indicators of a social cognitive map
Description
Table of graph indicators of a social cognitive map
Usage
GraphIndicatorsTable(df.graph.indic)
Arguments
df.graph.indic |
A data frame, as the output of the function 'GraphIndicators' |
Details
Table of graph indicators of a social cognitive map
Value
A data frame of graph thery indicator, easier to read (long format)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
df.graph.indic <- GraphIndicators(my.project)
GraphIndicatorsTable(df.graph.indic)
Individual Cognitive Mapping
Description
Formatting the data for plotting an Individual Cognitive Map
Usage
IndCMap(project, doc.id)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
doc.id |
The id of a document |
Value
a 'IndCMap' object, a list containing various information that could be use for plotting an Individual Cognitive Map. The most important elements are :
- "vertex"
A list of information on Cognitive Map's variables (i.e. vertices or concepts)
- "edg"
A list of information about relationships
- "graph"
A graphNEL object
- "eAttrs"
A list of graphical attributes of edges
- "nAttrs"
A list of graphical attributes of nodes (vertices)
- "gAttrs"
A list of graphical attributes of the whole graph
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
IndCMap(my.project, 1)
Import a Qualitatve Data Analysis project
Description
This function import and format the data from a coding tool in a Qualitatve Data Analysis.
Usage
ProjectCMap(main_path, project_name, coder = "qcoder", sep = ">")
Arguments
main_path |
The main to your QDA project. It must ended with '/' |
project_name |
The name of your project (as defined in 'qcoder', the name of the subfolder in your main_path). This name is also used in some filenames in the data_frame subsubfolders. |
coder |
A character string indicating the coding tool used for coding the QDA. The only tool supported now is 'qcoder'. Earlier version of cogmapr worked with "RQDA" project (no more maintened). |
sep |
(==Depreciated, with RQDA project==) A character string (often a single character) that is used in RQDA in order to express the relationships between two variables. Default is "_" if codes used in RQDA are of the form : "x_y" (i.e. relationship from x to y), but it is possible to use ">", "->", "–>" or even "—>" |
Details
This function import and format the data from a coding tool in a Qualitatve Data Analysis (QDA).
Value
A list
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
Extract all quotes of a QDA project
Description
Extract all quotes of a QDA project
Usage
QuotesCMap(project)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
Details
This function creates a data frame with all quotes of a Qualitative Data Analysis (QDA) project
Value
A data frame with relationships and quotes
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
QuotesCMap(my.project)
Extract all quotes of a document (or an Individual Cognitive Map)
Description
Extract all quotes of a document
Usage
QuotesIndCMap(project, doc.id)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
doc.id |
The id of a document (id of documents can be found in the data frame "documents" in the QDA project) |
Details
This function creates a data frame with all quotes of a one document of a Qualitative Data Analysis (QDA) project
Value
A data frame with relationships and quotes
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
QuotesIndCMap(my.project, 2)
Extract all quotes of documents (or a Social Cognitive Map)
Description
Extract all quotes of a group of documents (or of an Social Cognitive Map)
Usage
QuotesSocCMap(project, min.weight = 1, filters = NULL, units = "all")
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
Details
This function creates a data frame with all quotes of a a group of documents of a Qualitative Data Analysis (QDA) project
Value
A data frame of relationships and quotes
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
QuotesSocCMap(my.project)
QuotesSocCMap(my.project, units = 'Québec')
Compare relationships weight between maps
Description
This function test the differences between the properties of relationships
Usage
RelationshipTest(
project,
units,
output = "p.value",
weighted.icm = FALSE,
sep = ">",
coder = "qcoder"
)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
The units to compare |
output |
"p.value" (default) or "raw.data". |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
sep |
(==Depreciated, with RQDA project==) A character string (often a single character) that is used in RQDA in order to express the relationships between two variables. Default is "_" if codes used in RQDA are of the form : "x_y" (i.e. relationship from x to y), but it is possible to use ">", "->", "–>" or even "—>" |
coder |
A character string indicating the coding tool used for coding the QDA. The only tool supported now is 'qcoder'. Earlier version of cogmapr worked with "RQDA" project (no more maintened). |
Details
This function test the differences between the weight of relationships between groups of documents (i.e. between social cognitive maps). Till now, only two excluding groups can be tested (ex. document from one country vs another country, from a group of players vs another group of players). It is not possible to compare non exclusive groups (ex. map from one country vs map from one group of players, as some documents can be in the two groups!). For this test, the 'fisher.test' is done. If output = 'p.value', the function returns the results of the tests, one test for each relationships of the map. If output = 'raw.data', the function returns the raw data on which the tests are done, one data frame by concept. This option can be used to export data and perform other statistical tests.
If more then 2 groups, 'anova' can be used as test (to be confirmed).
Value
A data frame (if output = "p.value"), a list of data frame (if output = "raw.data").
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
## need more documents
RelationshipTest(my.project, units = c("Belgium", "Québec"))
Summary table on relationship comparisons
Description
Summary table on relationship comparisons
Usage
RelationshipTestSummary(project, units, limit.p.value = 0.05)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
The units to compare |
limit.p.value |
A numeric. |
Details
This function produce a summary table based on relationship comparisons and is reactive to a limit of p.value beyond which differences are considered as significant and are reported in the table
Value
A data frame
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
## Here 0.6 is used only for producing an output. No signif. diff. is reported.
RelationshipTestSummary(my.project, units = c("Belgium", "Québec"), 0.6)
Remove codings of a QDA project
Description
Remove codings of a QDA project
Usage
RemoveCodings(project, codings_id)
Arguments
project |
A QDA project (as created by the qcoder package) |
codings_id |
A vector of integer corresponding with the id of the codings to remove |
Details
This function removes one or many codings of a Qualitative Data Analysis (QDA) project. The codings are listed using the 'id' of codings.
Value
A QDA project
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
my.cleansed.project <- RemoveCodings(my.project, 1)
Social Cognitive Mapping
Description
Formatting the data for plotting an Social Cognitive Map
Usage
SocCMap(
data.edges.soc,
project,
label = "num",
minlen = 1,
fontsize = 16,
shape = "box"
)
Arguments
data.edges.soc |
A data.frame as produced by the EdgSocCMap function |
project |
A QDA project, a list as generated by the ProjectCMap function. |
label |
A character string that defines the text that will be print in the variables (vertex) of the cognitive maps. It can be "num", "name" or "numname" (which is of the form "NUM - Name"). The default is "num" |
minlen |
A graphical parameter that defines a relative lenght between the variable of the cognitive maps. See help from RGraphViz package. |
fontsize |
The fontsize of vertices (concepts), in r-base plot |
shape |
The shape of the verices (concepts), in r-base plot |
Value
a 'SocCMap' object, a list containing various information that could be use for plotting an Individual Cognitive Map. The most important elements are :
- "vertex"
A list of information on Cognitive Map's variables (i.e. vertices)
- "edg"
A list of information about relationships
##'
- "graph"
A graphNEL object
- "eAttrs"
A list of graphical attributes of edges
- "nAttrs"
A list of graphical attributes of nodes (vertices)
- "gAttrs"
A list of graphical attributes of the whole graph
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
edg.scm <- EdgSocCMap(my.project, min.weight=6, weighted.icm=TRUE)
SocCMap(edg.scm, my.project)
Coordinates of the vertices of a Cognitive Map
Description
Get the coordinates of the vertices of a Cognitive Map. The output of this function can be useful for plotting Cognitive Maps in a personalize ways (as with ggplot2 as done by the ggCMap function of this package)
Usage
coordCMap(soc.cmap, layoutType = "neato")
Arguments
soc.cmap |
An object of class SocCMap, as an output of the SocCMap function |
layoutType |
Type of graph. See detail in RGraphViz. Can be 'neato', 'dot', 'twopi', 'circo', and 'fdp'. The default is 'neato'. |
Value
A data frame with three variable :
- $vertex
The number of the vertex)
- $x
The x coordinate of the vertex
- $y
The y coordinate of the vertex
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
edg.scm <- EdgSocCMap(my.project, min.weight=6, weighted.icm=TRUE)
scm <- SocCMap(edg.scm, my.project, label = "name", shape = "plaintext")
coordCMap(scm)
Data collection for ggCMap
Description
Get all important data for plotting a Cognitive Map in ggplot
Usage
data.ggCMap(
project,
min.weight = 1,
filters = NULL,
units = "all",
weighted.icm = FALSE,
label = "name",
minlen = 1,
fontsize = 16,
shape = "box",
layoutType = "neato",
vertex.filter = NULL,
edge.filter = NULL,
limit.to.filters = FALSE,
level = 0
)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
label |
A character string that defines the text that will be print in the variables (vertex) of the cognitive maps. It can be "num", "name" or "numname" (which is of the form "NUM - Name"). The default is "num" |
minlen |
A graphical parameter that defines a relative lenght between the variable of the cognitive maps. See help from RGraphViz package. |
fontsize |
The fontsize of vertices (concepts), in r-base plot |
shape |
The shape of the verices (concepts), in r-base plot |
layoutType |
Type of graph. See detail in RGraphViz. Can be 'neato', 'dot', 'twopi', 'circo', and 'fdp'. The default is 'neato'. |
vertex.filter |
A vector of integers or characters given the 'id' of vertices (concepts) that will be included in the map. By default, all vertices are included (vertex.filter = NULL) |
edge.filter |
A vector of characters given the name "i~j" of edges (relationships from "i" to "j") that will be included in the map. By default, all edges are included (edge.filter = NULL) |
limit.to.filters |
A logical that will impact the position of the vertices. FALSE (the default) will filter vertices and edges (vertex.filter, edge.filter) keeping the position they would have in the unfiltered cognitive map (interesting with background). TRUE will fully re-compute the position of the vertices, building a cognitive map in its own (better readability). |
level |
0 or 1. Filter the edge/vertices at x level around the filtered edges/vertices (==Not implemented yet==) |
Details
Get all important data for plotting a Cognitive Map in ggplot
Value
A list of two data frames : -edges -vertex. In each of these data frames, the main columns are linked to the coordinates of vertex (x, y, x.from, y.from, x.to, y.to)
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
data.ggCMap(my.project)
data.ggCMap(my.project, min.weight = 3)
data.ggCMap(my.project, edge.filter = "4")
data.ggCMap(my.project, units = "Belgium")
Extract the quotes of a project linked to selected concepts
Description
Extract the quotes of a project linked to selected concepts
Usage
df.quotes.scm.concept(project, units, selected.concept)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
selected.concept |
A vector of character/integer value(s), the id(s) of one or many concept(s) of the map |
Details
Extract the quotes of a project linked to selected concepts. Units is a mandatory parameter as this function was initially developed for given the quotes linked to significantly different concepts between groups of documents (i.e. units).
Value
A data frame of relationships and quotes
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
df.quotes.scm.concept(my.project, "Québec", 4)
df.quotes.scm.concept(my.project, "Québec", "2")
Extract the quotes of a project linked to selected relationships
Description
Extract the quotes of a project linked to selected relationships
Usage
df.quotes.scm.edge(project, units, selected.edge)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
selected.edge |
A vector of character value(s), the names of one or many relationship(s) of the map |
Details
Extract the quotes of a project linked to selected relationships. Units is a mandatory parameter as this function was initially developed for given the quotes linked to significantly different relationships between groups of documents (i.e. units).
Value
A data frame of relationships and quotes
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
df.quotes.scm.edge(my.project, "Belgium", "1~2")
Plot a social cognitive map using ggplot2
Description
Plotting the a social cognitive map using ggplot2
Usage
ggCMap(
data,
size.concepts = 4,
size.labels = 4,
size.edges = 4,
size.arrows = 4,
alpha.arrows = 0.3
)
Arguments
data |
A list, the output of the 'data.ggCMap' function, containing all useful vertex and edge information for the cognitive maps. |
size.concepts |
Size of the dot linked to vertices |
size.labels |
Size of the labels of vertices |
size.edges |
Size of the labels of the weight of edges |
size.arrows |
Size of arrows (head) |
alpha.arrows |
The transparency of arrows. |
Details
Plotting the a social cognitive map using ggplot2
Value
A ggplot of a social cognitive map
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
df.scm <- data.ggCMap(my.project, edge.filter = "4")
ggCMap(df.scm)
Ghost cognitive map
Description
ggplot background of a map (used in highlighted maps)
Usage
ggCMap.bg(
data,
size.concepts = 4,
size.labels = 4,
size.edges = 4,
size.arrows = 4,
map.color = "grey50"
)
Arguments
data |
A list, the output of the 'data.ggCMap' function, containing all useful vertex and edge information for the cognitive maps. |
size.concepts |
Size of the dot linked to vertices |
size.labels |
Size of the labels of vertices |
size.edges |
Size of the labels of the weight of edges |
size.arrows |
Size of arrows (head) |
map.color |
The unique color of all concepts and labels of the ghost map |
Details
ggplot background of a map (used in highlighted maps). It is like a ghost map.
Value
A plot
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
df.scm <- data.ggCMap(my.project, edge.filter = "4")
ggCMap.bg(df.scm)
Highlighted cognitive map
Description
A cognitive map where some concepts or relationships are highlighted
Usage
ggCMap.hl(
project,
min.weight = 1,
filters = NULL,
units = "all",
weighted.icm = FALSE,
label = "name",
minlen = 1,
fontsize = 16,
shape = "box",
layoutType = "neato",
vertex.filter = NULL,
edge.filter = NULL,
limit.to.filters = FALSE,
level = 0,
size.concepts = 4,
size.labels = 4,
size.edges = 4,
size.arrows = 4,
alpha.arrows = 0.3,
map.color = grDevices::grey(0.8)
)
Arguments
project |
A QDA project, a list as generated by the ProjectCMap function. |
min.weight |
A integer that will determine the minimum (>=) weight of relationships that will be taken into account. Relationships with a lower weight (<) will not be shown. Default is set to 1 (i.e. all relationships are shown). |
filters |
A list of named strings that will filter the relationships showed in the SCM. e.g. =list(coding_class = "A_coding_class", document_part = "A_document_part")=. To date, these filters are linked to the nature of relationships. |
units |
A string vector giving the names of the units (i.e. classes linked to documents) that will be include in the SCM. It is a second type of filter. |
weighted.icm |
A boolean. If FALSE, the weight of the relationships in the ICM will be fixed to 1. |
label |
A character string that defines the text that will be print in the variables (vertex) of the cognitive maps. It can be "num", "name" or "numname" (which is of the form "NUM - Name"). The default is "num" |
minlen |
A graphical parameter that defines a relative lenght between the variable of the cognitive maps. See help from RGraphViz package. |
fontsize |
The fontsize of vertices (concepts), in r-base plot |
shape |
The shape of the verices (concepts), in r-base plot |
layoutType |
Type of graph. See detail in RGraphViz. Can be 'neato', 'dot', 'twopi', 'circo', and 'fdp'. The default is 'neato'. |
vertex.filter |
A vector of integers or characters given the 'id' of vertices (concepts) that will be included in the map. By default, all vertices are included (vertex.filter = NULL) |
edge.filter |
A vector of characters given the name "i~j" of edges (relationships from "i" to "j") that will be included in the map. By default, all edges are included (edge.filter = NULL) |
limit.to.filters |
A logical that will impact the position of the vertices. FALSE (the default) will filter vertices and edges (vertex.filter, edge.filter) keeping the position they would have in the unfiltered cognitive map (interesting with background). TRUE will fully re-compute the position of the vertices, building a cognitive map in its own (better readability). |
level |
0 or 1. Filter the edge/vertices at x level around the filtered edges/vertices (==Not implemented yet==) |
size.concepts |
Size of the dot linked to vertices |
size.labels |
Size of the labels of vertices |
size.edges |
Size of the labels of the weight of edges |
size.arrows |
Size of arrows (head) |
alpha.arrows |
The transparency of arrows. |
map.color |
The unique color of all concepts and labels of the ghost map |
Details
A cognitive map where some concepts or relationships are highlighted. The highlighted elements are those who are filtered (see edge.filter, vertex.filter). A background (ghost map) will be show by default. The parameter 'limit.to.filters' can be set as 'TRUE' for only showing the filtered elements.
Value
A plot
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
ggCMap.hl(my.project, vertex.filter = 2)
Plotting an Individual Cognitive Map
Description
Plotting an Individual Cognitive Map
Usage
plotIndCMap(
ind.cmap,
layoutType = "neato",
main = paste("Individual map -", ind.cmap[["agent"]][["name"]]),
...
)
Arguments
ind.cmap |
An object of class IndCMap, as an output of the IndCMap function |
layoutType |
Type of graph. See detail in RGraphViz. Can be 'neato', 'dot', 'twopi', 'circo', and 'fdp'. The default is 'neato'. |
main |
The title of the map. By default it is "Individual map - Agent's name" |
... |
other graphical parameters |
Value
A plot
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
icm <- IndCMap(my.project, 1)
plotIndCMap(icm)
Plotting a Social Cognitive Map
Description
Plotting a Social Cognitive Map
Usage
plotSocCMap(soc.cmap, layoutType = "neato", ..., main = "Social map")
Arguments
soc.cmap |
An object of class SocCMap, as an output of the SocCMap function |
layoutType |
Type of graph. See detail in RGraphViz. Can be 'neato', 'dot', 'twopi', 'circo', and 'fdp'. The default is 'neato'. |
... |
other graphical parameters |
main |
The title of the map. By default it is "Individual map - Agent's name" |
Value
A plot
Examples
project_name <- "a_new_project"
main_path <- paste0(system.file("testdata", package = "cogmapr"), '/')
my.project <- ProjectCMap(main_path, project_name)
edg.scm <- EdgSocCMap(my.project, min.weight=6, weighted.icm=TRUE)
scm <- SocCMap(edg.scm, my.project)
plotSocCMap(scm)
scm <- SocCMap(edg.scm, my.project, label = "name", shape = "plaintext")
plotSocCMap(scm)