| Title: | Tools for Text Analysis of Aesop's Fables |
|---|---|
| Description: | Provides a tidy text corpus of Aesop's Fables sourced from the Library of Congress, along with analysis-ready datasets for sentiment, emotion, and linguistic analysis of moral storytelling. The package includes both full narrative texts and word-level representations to support exploratory text analysis and teaching workflows. |
| Authors: | Dave Brocker [aut, cre] |
| Maintainer: | Dave Brocker <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0 |
| Built: | 2026-05-26 08:57:05 UTC |
| Source: | https://github.com/davidbrocker/aesopr |
A token-level dataset of Aesop's Fables joined with the AFINN sentiment lexicon. Each row represents a word from a fable that appears in the AFINN lexicon, along with its associated numeric sentiment score.
data(aesops_afinn)data(aesops_afinn)
A tibble with one row per token and sentiment match, containing:
Character identifier for the fable
Title of the fable
The moral or lesson associated with the fable.
Tokenized word from the fable text
AFINN sentiment score
The AFINN lexicon assigns integer sentiment values ranging from negative to positive polarity, making this dataset well-suited for aggregated sentiment scoring and comparative analyses across fables.
AFINN sentiment lexicon by Finn Årup Nielsen (2011).
Nielsen, F. Å. (2011). *A new ANEW: Evaluation of a word list for sentiment analysis in microblogs*. Proceedings of the ESWC Workshop on Making Sense of Microposts.
A token-level dataset of Aesop's Fables joined with the Bing Liu sentiment lexicon. Each row represents a word from a fable that appears in the Bing lexicon, labeled with binary sentiment polarity.
data(aesops_bing)data(aesops_bing)
A tibble with one row per token and sentiment match, containing:
Character identifier for the fable
Title of the fable
Tokenized word from the fable text
Binary sentiment label ("positive" or "negative")
The Bing lexicon classifies words as either "positive" or
"negative", making this dataset useful for polarity-based
sentiment summaries and instructional demonstrations.
Bing Liu sentiment lexicon.
Hu, M., & Liu, B. (2004). *Mining and summarizing customer reviews*. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
A dataset containing 147 of Aesop's Fables retrieved from the Library of Congress public domain collection.
A dataset containing 147 of Aesop's Fables retrieved from the Library of Congress public domain collection.
aesops_fables aesops_fablesaesops_fables aesops_fables
A tibble with 147 rows and the following variables:
Character string uniquely identifying the fable
(e.g., "001", "075").
Title of the fable.
Full narrative text of the fable.
The moral or lesson associated with the fable.
URL of the original Library of Congress page.
A tibble with 147 rows and the following variables:
Character string uniquely identifying the fable
(e.g., "001", "075").
Title of the fable.
Full narrative text of the fable.
The moral or lesson associated with the fable.
URL of the original Library of Congress page.
Each row represents a single fable and includes metadata, the full narrative text, and the associated moral.
The texts were scraped from https://read.gov/aesop/ and are believed to be in the public domain. Text has been minimally cleaned to preserve original phrasing and narrative structure.
Each row represents a single fable and includes metadata, the full narrative text, and the associated moral.
The texts were scraped from https://read.gov/aesop/ and are believed to be in the public domain. Text has been minimally cleaned to preserve original phrasing and narrative structure.
Library of Congress, “Aesop's Fables”
Library of Congress, “Aesop's Fables”
aesops_fables if (requireNamespace("dplyr", quietly = TRUE)) { aesops_fables |> dplyr::filter(fable_id == "075") |> dplyr::select(title, moral) } aesops_fables aesops_fables |> dplyr::filter(fable_id == "075") |> dplyr::select(title, moral)aesops_fables if (requireNamespace("dplyr", quietly = TRUE)) { aesops_fables |> dplyr::filter(fable_id == "075") |> dplyr::select(title, moral) } aesops_fables aesops_fables |> dplyr::filter(fable_id == "075") |> dplyr::select(title, moral)
A tidy token-level dataset derived from aesops_fables, where each row represents a single word token from a fable.
A tidy token-level dataset derived from aesops_fables,
where each row represents a single word token from a fable.
aesops_tokens aesops_tokensaesops_tokens aesops_tokens
A tibble with one row per word token and the following variables:
Character string identifying the source fable.
Lowercase word token extracted from the fable text.
Total number of words in the source fable.
URL of the original fable text.
A tibble with one row per word token and the following variables:
Character string identifying the source fable.
Title of the fable
The moral or lesson associated with the fable.
Lowercase word token extracted from the fable text.
This dataset is intended for text analysis tasks such as sentiment analysis, n-gram modeling, and word frequency analysis.
Tokens were generated using tidytext::unnest_tokens().
Stop words have not been removed, allowing users full flexibility in
preprocessing decisions.
This dataset is intended for text analysis tasks such as sentiment analysis, n-gram modeling, and word frequency analysis.
Tokens were generated using tidytext::unnest_tokens().
Stop words have not been removed, allowing users full flexibility
in preprocessing decisions.
aesops_tokens if (requireNamespace("dplyr", quietly = TRUE)) { aesops_tokens |> dplyr::count(word, sort = TRUE) } aesops_tokens aesops_tokens |> dplyr::count(word, sort = TRUE)aesops_tokens if (requireNamespace("dplyr", quietly = TRUE)) { aesops_tokens |> dplyr::count(word, sort = TRUE) } aesops_tokens aesops_tokens |> dplyr::count(word, sort = TRUE)