Package: themescopeR 0.1.1

themescopeR: Social Representation Analysis via Semantic Network Mapping

Implements the ThemeScope framework for detecting and visualising social representations in large-scale digital text corpora. From raw documents it builds, via 'udpipe' annotation, sentence-level word co-occurrence networks and derives two community-level indicators grounded in Social Representation Theory: the Prototypical Salience Index (PSI) for anchoring and the Concreteness Score (CS) for objectification. Communities are located in a two-dimensional, theoretically grounded representational map. The whole pipeline is usable from the R console; an optional 'shiny' graphical interface calls the same exported functions. The method is described in Misuraca, Spano and D'Aniello (2026) <doi:10.1177/01655515261454276>.

Authors:Luca D'Aniello [aut, cre], Michelangelo Misuraca [aut], Maria Spano [aut]

themescopeR_0.1.1.tar.gz
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themescopeR_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
themescopeR/json (API)

# Install 'themescopeR' in R:
install.packages('themescopeR', repos = c('https://lucadaniello.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lucadaniello/themescoper/issues

Datasets:
  • brysbaert - Brysbaert et al. (2014) concreteness norms

On CRAN:

Conda:

computational-social-sciencecontent-analysisdiscourse-analysisnetwork-analysissemanitic-analysissocial-representation-theorythematic-analysisthemescope

3.54 score 3 scripts 309 downloads 33 exports 45 dependencies

Last updated from:1a1eb94556. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK172
source / vignettesOK273
linux-releaseOK165
macos-releaseOK189
macos-oldrelOK221
windows-develOK101
windows-releaseOK103
windows-oldrelOK87
wasm-releaseOK153

Exports:assign_quadrantbuild_cooccurrence_matrixbuild_cooccurrence_networkbuild_vocabcompute_association_strengthcompute_coherencecompute_cscompute_network_statscompute_psidetect_communitiesget_community_subgraphslexicon_coveragematch_concretenessnormalize_cooccurrenceplot_networkplot_themescopepreprocess_textsread_collectionread_themescopesave_themescopeterm_relevancethemescopethemescope_appthemescope_cache_dirthemescope_coloursthemescope_progresstop_termsts_clear_cachets_download_modelts_list_modelsts_model_pathvalidate_words_dfzscore

Dependencies:bitbit64cellrangerclicliprcpp11crayondata.tabledplyrfarvergenericsggplot2ggrepelgluegtablehmsigraphisobandlabelinglatticelifecyclemagrittrMatrixpillarpkgconfigprettyunitsprogressR6RColorBrewerRcppreadrreadxlrematchrlangS7scalestibbletidyselecttzdbudpipeutf8vctrsviridisLitevroomwithr

Readme and manuals

Help Manual

Help pageTopics
Assign quadrant labels from z-scored PSI and CSassign_quadrant
Brysbaert et al. (2014) concreteness normsbrysbaert
Build a co-occurrence (similarity) matrixbuild_cooccurrence_matrix
Build a thresholded semantic co-occurrence networkbuild_cooccurrence_network
Build a vocabulary data frame from an annotated words data framebuild_vocab
Compute Association Strength from a co-occurrence matrixcompute_association_strength
Compute edge-density coherence per communitycompute_coherence
Compute the Concreteness Score (CS) per communitycompute_cs
Compute network-level and community-level statisticscompute_network_stats
Compute the Prototypical Salience Index (PSI) per communitycompute_psi
Detect communities in a semantic networkdetect_communities
Extract community subgraphsget_community_subgraphs
Concreteness lexicon coverage diagnosticslexicon_coverage
Match terms to a concreteness lexiconmatch_concreteness
Normalise a co-occurrence matrix into a similarity matrixnormalize_cooccurrence
Plot a community-coloured semantic network (igraph)plot_network
Create a ThemeScope representational mapplot_themescope
Annotate a document collection with udpipepreprocess_texts
Read a document collection into a tidy data frameread_collection
Read a '.themescope' archiveprint.themescope_archive read_themescope summary.themescope_archive
Save an analysis as a '.themescope' archivesave_themescope
Compute term relevance within communitiesterm_relevance
Run the full ThemeScope analysis pipelineas.data.frame.themescope plot.themescope print.themescope summary.themescope themescope
Launch the themescopeR Shiny applicationthemescope_app
Location of the themescopeR model cachethemescope_cache_dir
ThemeScope pastel colour palettethemescope_colours
Top terms per communitytop_terms
Delete cached language modelsts_clear_cache
Download and cache an updated udpipe language modelts_download_model
List the available updated language modelsts_list_models
Resolve the cached path of an updated udpipe modelts_model_path
Validate an annotated words data framevalidate_words_df
Compute z-scoreszscore