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.
This is a simple tool for text dataset analysis and multiple datasets comparison. Keywords: corpus, text dataset, text distribution, part-of-speech(pos), zipf's-law, distinct value, concreteness
This code takes an English word as input and returns its concreteness score and position of speech, using as reference the Brysbaert, M. et. al. (2014) concreteness ratings for 40 thousand generally known English word lemmas.
To build a regression model to predict the concrete compressive strength based on the different features in the training data.
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