The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling

This repository contains the main code for the paper “The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling” by M. H. Asnawi et al. (2023).

Authors and Affiliations

Mohammad Hamid Asnawi¹, Anindya Apriliyanti Pravitasari¹, Tutut Herawan², Triyani Hendrawati¹

1. Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Bandung 45363, Indonesia
2. Department of Information Systems, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia

Dataset

We have released the "User Feedback Dataset from the Top 15 Downloaded Mobile Applications." The dataset is available on Zenodo. If you use the dataset, please cite both the dataset and the paper

Requirements

To run the code/notebook in this repository, you'll need the following dependencies:

• Python 3.9.13 or later
• Additional requirements are specified in the requirements.txt file.

You can install the required packages using the following command:

pip install -r requirements.txt

Citation (BibTeX)

Paper - "The The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling"

@ARTICLE{10318123,
  author={Asnawi, Mohammad Hamid and Pravitasari, Anindya Apriliyanti and Herawan, Tutut and Hendrawati, Triyani},
  journal={IEEE Access}, 
  title={The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling}, 
  year={2023},
  volume={11},
  number={},
  pages={130272-130286},
  doi={10.1109/ACCESS.2023.3332644}}

}

Dataset - "User Feedback Dataset from the Top 15 Downloaded Mobile Applications"

@article{---,
  author = {Asnawi, Mohammad Hamid and Pravitasari, Anindya Apriliyanti and Herawan, Tutut and Hendrawati, Triyani},
  title = {User Feedback Dataset from the Top 15 Downloaded Mobile Applications},
  journal = {The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling},
  volume = {11},
  pages = {130272--130286},
  year = {2023},
  month = nov,
  publisher = {Zenodo},
  doi = {10.5281/zenodo.10204232},
}