Minimal Dataset and Code for: Social friction vs. Cognitive efficiency: A comparative analysis of help-seeking behaviors in human communities and generative AI

This repository contains the minimal dataset and author-generated Python code required to replicate the findings of the study: "Social friction vs. Cognitive efficiency: A comparative analysis of help-seeking behaviors in human communities and generative AI," submitted to PLOS ONE.The replication package includes:matched_corpus_N30000.csv: The complete, propensity-score-matched dataset consisting of 30,000 dialogue turns from LMSYS-Chat-1M (Human-AI) and Stack Exchange (Human-Human).analysis_and_figures_code.py: A comprehensive Python script used for text preprocessing, linguistic feature extraction (Hedges, Politeness markers, Vulnerability metrics, etc.), statistical analysis, and high-resolution figure generation.All data processing follows standard computational sociolinguistic protocols to ensure full transparency and reproducibility of the research.