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Temporal Topic Modelling (Topic Evolution Analysis) using the Pachinko Allocation model

License: MIT License

Jupyter Notebook 99.70% Python 0.30%
machine-learning nlp pachinko-allocation python topic-modeling topic-evolution

temporaltopicmodelling-pachinko's Introduction

Temporal Topic Modelling with Pachinko Allocation

This repository contains code for the modelling part of the "A Sustainable West? Analyzing Clusters of Public Opinion in Sustainability Western Discourses in a Collection of Multilingual Newspapers (1999-2018)" paper.

Content

It includes code for the Topic Modelling, Topic Clustering and Topic Evolution.

  1. pachinko_model.ipynb uses the Pachinko Allocation model to find topics in a set of documents (it also contains information on the finetuning of parameters and sentiment analysis,
  2. topic_similarity.ipynb analyzes the relationships between the topics of different corpora (that were identified by PA model, you can apply same pipeline to other Topic Modelling Models) - topic similarity, topic clustering, topic evolution and sentiment analysis.

How to cite

Zenodo Preprint

@article{fernandez2023sustainable,
  author       = {Elena Fernández Fernández and Germans Savcisens},
  title        = {{"A Sustainable West? Analyzing Clusters of Public Opinion in Sustainability Western Discourses in a Collection of Multilingual Newspapers (1999-2018)"}},
  month        = mar,
  year         = 2023,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.7742461},
  url          = {https://doi.org/10.5281/zenodo.7742461}
}

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