r-text.org valid

text

### 📣 Online Workshop: *Analysing Human Language using R*

For agents: Documentation for the R 'text' package for language analysis: word embeddings, Hugging Face LLM access, and psychological assessment models.

r packagetext analysisword embeddingslarge language modelspsychological assessmenthugging face

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-24T09:16:28.346Z. Cached copy · Source on r-text.org

# text

## R Language Analysis Suite

An R-package for analyzing natural language with transformers-based
large language models. The `text` package is part of the *R Language
Analysis Suite*, including:

- [`talk`](https://www.r-talk.org/) - a package that transforms voice
  recordings into text, audio features, or embeddings.\
  \
- [`text`](https://www.r-text.org/) - a package that provides tools for
  many language tasks such as converting digital text into word
  embeddings.\
  \
  `talk` and `text` offer access to Large Language Models from Hugging
  Face.\
  \
- [`topics`](https://www.r-topics.org/) a package with tools for
  visualizing language patterns into topics.\
  \
- [`the L-BAM Library`](https://r-text.org/articles/LBAM.html) a library
  that provides pre-trained models for different psychological
  assessments such as mental health issues, personality and related
  behaviours.\
  \

![](reference/figures/talk_text_topics.svg)

\
The *R Language Analysis Suite* is created through a collaboration
between psychology and computer science to address research needs and
ensure state-of-the-art techniques. The suite is continuously tested on
Ubuntu, Mac OS and Windows using the latest stable R version.

The *text*-package has two main objectives:\
\* First, to serve R-users as a *point solution* for transforming text
to state-of-the-art word embeddings that are ready to be used for
downstream tasks. The package provides a user-friendly link to language
models based on transformers from [Hugging
Face](https://huggingface.co/).\
\* Second, to serve as an *end-to-end solution* that provides
state-of-the-art AI techniques tailored for social and behavioral
scientists.\
Please reference our tutorial article when using the `text` package:
[The text-package: An R-package for Analyzing and Visualizing Human
Language Using Natural Language Processing and Deep
Learning](https://pubmed.ncbi.nlm.nih.gov/37126041/).\

> ### 📣 Online Workshop: *Analysing Human Language using R*
>
> **August 11–13, 2026** — three half-day sessions (2:00–5:00 pm CEST /
> 8:00–11:00 am ET)
>
> Learn the full *R Language Analysis Suite* —
> [`talk`](https://www.r-talk.org/), [`text`](https://www.r-text.org/),
> and [`topics`](https://www.r-topics.org/) — with Oscar Kjell.
>
> **[Read more & register →](https://smart-workshops.com/lang-r-info)**
…

Related sites

Explore similar publishers →

Similar publisher descriptions and documentation. Similarity does not imply affiliation or equivalent capabilities.

Machine-readable: GET /v1/resolve?q=r-text.org · GET /v1/domain/r-text.org · this page as Accept: application/json or text/markdown · MCP lookup_domain

Automatically discovered from public files. Inclusion does not imply endorsement or publisher participation.

Claim my listing on Agent Web Map for r-text.org:
1. POST https://agentwebmap.com/v1/sites/r-text.org/claims and keep claim_id and claim_secret private.
2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://r-text.org/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
3. POST https://agentwebmap.com/v1/sites/r-text.org/verify with {"claim_id": "...", "claim_secret": "..."}.
4. Save the api_key from the answer; it manages the listing (PATCH https://agentwebmap.com/v1/sites/r-text.org).
MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

Corrections or removal requests: contact the directory.