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https://github.com/aieng-lab/replication-kit-qtgpt-study

https://github.com/aieng-lab/replication-kit-qtgpt-study

Science Score: 13.0%

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    CITATION.cff file
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    Low similarity (9.3%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: aieng-lab
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 8.18 MB
Statistics
  • Stars: 0
  • Watchers: 3
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License

README.md

Replication package

This repository contains the code and data in a study on the ability of large language models to impersonate public speakers in political debates.

Requirements

  • Python 3 (tested with Python 3.10)

Structure

  • data/: Contains the data used in the experiments, including the debate questions, answers, generated answers, speaker biographies, linguistic markers, code book of the free text answers, and the results of the manual coding.
  • figures/: Contains the figures generated in the analysis.
  • markers/: Contains helper files with lists of linguistic markers required for the calcuation of the linguistic surface.
  • statistical_analysis.ipynb: Jupyter notebook with the statistical analysis of the data.
  • calclingusticfeatures.ipynb: Jupyter notebook with the code to calculate the linguistic features that describe the linguistic surface.

Usage example for Ubuntu 22.04

Exectute the following commands in the terminal to clone the repository and install the required packages.

bash git clone git@github.com:aieng-lab/replication-kit-qtgpt-study.git cd replication-kit-qtgpt-study python3 -m venv venv source venv/bin/activate pip install -r requirements.txt

You can then start Jupyter Lab and open it in a browser to view and execute the Juypter notebooks.

bash jupyter lab

Owner

  • Name: aieng-lab
  • Login: aieng-lab
  • Kind: organization

GitHub organization of the Chair for AI Engineering of the University of Passau

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Dependencies

requirements.txt pypi
  • jupyterlab *
  • lexicalrichness ==0.5.1
  • matplotlib ==3.8.4
  • numpy ==1.26.4
  • pandas ==2.2.2
  • pingouin ==0.5.4
  • scipy ==1.13.0
  • seaborn ==0.13.2
  • spacy ==3.7.5
  • statsmodels ==0.14.2