dynamic_topic_modeling

Dynamic Topic Modeling (DTM)(Blei and Lafferty 2006) is an advanced machine learning technique for uncovering the latent topics in a corpus of documents over time. The goal of this project is to provide an easy-to-use Python package for running DTM. This package is built on the frameworks of sklearn and gensim(Wang 2018; Svitlana 2019) for Dynamic Topic Modeling.

To get started, follow the tutorials on our Jupyter notebooks:

1. LDA based on sklearn
2. LDA based on gensim
3. Dynamic Topic Modeling
4. Data Analysis on Demi Gods and Semi Devils using Dynamic Topic Modeling

Install

pip install dynamic_topic_modeling

Citations

If you use dynamic_topic_modeling, please cite:

Jiaxiang Li. (2020, February 9). JiaxiangBU/dynamic_topic_modeling: dynamic_topic_modeling 1.1.0 (Version v1.1.0). Zenodo. http://doi.org/10.5281/zenodo.3660401

@software{jiaxiang_li_2020_3660401,
  author       = {Jiaxiang Li},
  title        = {{JiaxiangBU/dynamic_topic_modeling: 
                   dynamic_topic_modeling 1.1.0}},
  month        = feb,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {v1.1.0},
  doi          = {10.5281/zenodo.3660401},
  url          = {https://doi.org/10.5281/zenodo.3660401}
}

**Code of Conduct**

Please note that the `dynamic_topic_modeling` project is released with a [Contributor Code of Conduct](https://github.com/JiaxiangBU/dynamic_topic_modeling/blob/master/CODE_OF_CONDUCT.md).
By contributing to this project, you agree to abide by its terms.

**License**

Apache License © [Jiaxiang Li;Shuyi Wang;Svitlana Galeshchuk](https://github.com/JiaxiangBU/dynamic_topic_modeling/blob/master/LICENSE.md)

Blei, David M., and John D. Lafferty. 2006. “Dynamic Topic Models.” In Machine Learning, Proceedings of the Twenty-Third International Conference (ICML 2006), Pittsburgh, Pennsylvania, USA, June 25-29, 2006.

Svitlana. 2019. “Dtmvisual: This Package Consists of Functionalities for Dynamic Topic Modelling and Its Visualization.” GitHub. 2019. https://github.com/GSukr/dtmvisual.

Wang, Shuyi. 2018. “Wei_lda_debate:” GitHub. 2018. https://github.com/wshuyi/wei_lda_debate.