PsychiatryNLPKit.analysis.pronoun_ratio

PsychiatryNLPKit.analysis.pronoun_ratio(pos_tags, sections=None, lang='en', averaging_method='macro')[source]

Pronoun-to-total-word ratio per section.

Notes:

Theoretical basis - High pronoun count predicts higher semantic similarity scores (He et al., 2024). Excessive pronoun use may reflect vague or deictic language patterns.

Args:

pos_tags: Dict mapping section names to lists of POS-tagged sentences. sections: Sections to process. None processes all sections in

pos_tags.

lang: Language code (“en” or “fr”). averaging_method: "macro" averages per-sentence ratios; "micro"

computes total pronouns / total words across the section.

Returns:

Dict mapping section names to a dict with keys "pronoun_ratio" and "pronoun_count". Empty sections receive float("nan") for both.

References:

He, R., Palominos, C., Zhang, H., Alonso-Sánchez, M. F., Palaniyappan, L., & Hinzen, W. (2024). Navigating the semantic space: Unraveling the structure of meaning in psychosis using different computational language models. Psychiatry Research, 333, 115752. https://doi.org/10.1016/j.psychres.2024.115752