wordtangible 0.1.0

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WordTangible

WordTangible is a Python library for analyzing the concreteness and imageability of words and text. It provides tools to measure how abstract or concrete the language in a given text is, which can be useful for various natural language processing tasks, readability analysis, and linguistic research.

Features

• Get concreteness ratings for individual words
• Calculate average concreteness for a given text
• Compute the ratio of concrete to abstract words in a text
• Customizable thresholds for concrete and abstract word classification
• Option to include or exclude stopwords in analysis

Installation

You can install WordTangible using pip:

pip install wordtangible

Usage

Here are some basic examples of how to use WordTangible:

from wordtangible import word_concreteness, avg_text_concreteness, concrete_abstract_ratio

# Get concreteness rating for a single word
print(word_concreteness("apple"))  # Output: 5.0 (highly concrete)

# Calculate average concreteness of a text
text = "The abstract concept of love is as tangible as the apple in your hand."
print(avg_text_concreteness(text))  # Output: ~3.5 (mix of concrete and abstract)

# Get the ratio of concrete to abstract words
print(concrete_abstract_ratio(text))  # Output: ~1.0 (balanced concrete and abstract words)

For more detailed usage instructions and API documentation, please refer to our documentation.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• The concreteness ratings are derived from multiple sources, including the MRC Psycholinguistic Database, Brysbaert et al. concreteness ratings, and Glasgow concreteness ratings.
• This project uses NLTK for tokenization and stopword filtering.

Citation

If you use WordTangible in your research, please cite it as follows:

Robison, J. (2024). WordTangible: A Python library for word concreteness and imageability analysis. [Software]. Available from https://github.com/jrrobison1/wordtangible