R Observatory: Metrics for themescopeR version 0.1.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

themescopeR

0.1.1Package record

Social Representation Analysis via Semantic Network Mapping

0packages depend

631downloads / year

66.6%test coverage

13/13flavors OK

Overview

About

Maintained by Luca D'AnielloCRAN page ↗GitHub ↗Issues ↗

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.

Changes in 0.1.1

Changes made in response to the CRAN review of 0.1.0.

themescope_cache_dir() no longer creates anything: it reports where models would be cached, and gained a create argument (default FALSE). The cache directory is created only when a model is actually downloaded.
ts_download_model() and ts_model_path() take model_dir = NULL instead of defaulting to a path under the user's home filespace. Pass a directory of your own, for instance tempdir(), to keep a download inside the session.
New ts_clear_cache() deletes the downloaded models and the cache directory, so everything the package stores on disk can be removed again.
The first download reports where it is caching.
Examples no longer use \dontrun{}. Those that need an internet connection use \donttest{} and fail gracefully, the Shiny launcher is guarded by if (interactive()), and every example that writes does so in tempdir().

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("themescopeR", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("lucadaniello/themescopeR")

Development version from lucadaniello/themescopeR. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-themescoper

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-themescopeR

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-themescopeR

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.0 min · r-oldrel-windows-x86_64

Status changes

OK13 OKNow
OK6 OK2026-08-21

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1.1

READMEYes · 1,810 wordsVignettesNoNEWSYes · 100% structured · mentions 0.1.1Citation fileYes · cites a publicationWebsitenot declared in DESCRIPTION

Help pages: 35 (2 internal)includes a package overview page
Examples that run: 91%30 run in a plain check (1 of them under a condition) · 3 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples: 97%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 3%

How these are measured

Downloads

631

CRAN downloads in the past year

Rank #20,619 · ~2/day · ~53/mo

Releases R versions

Daily download trend is not available in this view yet.

28730 days

63190 days

6311 year

Compare downloads with other packages →

Also on15 r2u6 autocran

How downloads are counted

Repository

lucadaniello/themescoper ↗Account: lucadaniello

0Stars

1Forks

0Open issues

0Open PRs

0Releases

17Commits

1Commit identities

network-analysissemanitic-analysissocial-representation-theorythemescopecomputational-social-sciencecontent-analysisdiscourse-analysisthematic-analysis

17 commits · Last activity 2026-08-23

Responsiveness

How these are sampled

PRs merged (all time): not measured
Median days to close, 50 most recently updated closed issues: 7
Median days to close, 50 most recently updated closed PRs: not measured

Issues over time

2026-08-21 · 12026-08-24 · 0

How these are measured

PracticesBeta

6 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/lucadaniello/themescoper on 2026-10-11.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Reproducibility and dev environment (1)

data-raw/

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies

21 external dependencies (excludes base and recommended)

Installing themescopeR adds 43 packages (23 with compiled code, 36 MB of source tarballs). Heaviest: ggplot2 6.0 MB, data.table 5.7 MB, igraph 4.8 MB.

Depends (1)

R >= 4.1.0

Imports (14)

cli dplyr ggplot2 ggrepel igraphMatrixmethodsreadr readxl rlangstatstoolsudpipeutils

LinkingTo (0)

none

Suggests (12)

bslib DT ggraph htmltools knitr plotly rmarkdown shiny shinycssloaders testthat visNetwork writexl

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (3)

Luca D'Aniello

Author, Maintainer since 0.1.1 (2026)

Michelangelo Misuraca

Author

Maria Spano

Author

Releases (1)

0.1.1Latest
record
2026-08-20 · current release
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-08-20
Total releases: 1 / 1 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.1.0
Bundled data: 180 KB / 1 file
Download size: 1.1 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("themescopeR")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1177/01655515261454276.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for themescopeR version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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