Package: dynamic-topic-modeling
dynamic_topic_modelingRun dynamic topic modeling.The goal of 'wei_lda_debate' is to build Latent Dirichlet Allocation
models based on 'sklearn' and 'gensim' framework, and Dynamic Topic
Model(Blei and Lafferty 2006) based on 'gensim' framework. I decide to
build a Python package 'dynamic_topic_modeling', so this reposority
will be updated and 'wei_lda_debate' is depreciated. The new
reposority path ishttps://github.com/JiaxiangBU/dynamic_topic_modeling.git.To build this package, I borrow from'wei_lda_debate'(Wang 2018) to build LDA framework'dtmvisual'(Svitlana 2019) to build the visualization framework.
Moreover, this package seems like a visualiztaion tutorial using
jupyter notebook for 'dtmvisual'.LDA based on
sklearnLDA based on
gensimDynamic Topic
ModelingData Analysis on Demi Gods and Semi Devils using Dynamic Topic
ModelingJiaxiang 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}
}If you use dynamic_topic_modeling, I would be very grateful if you can
add a citation in your published work. By citing
dynamic_topic_modeling, beyond acknowledging the work, you contribute
to make it more visible and guarantee its growing and sustainability.
For citation, please use the BibTex or the citation content.Installpip install dynamic_topic_modelingHow to useLDA based on
sklearnLDA based on
gensimDynamic Topic
ModelingData Analysis on Demi Gods and Semi Devils using Dynamic Topic
ModelingJiaxiang 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}
}If you use dynamic_topic_modeling, I would be very grateful if you can
add a citation in your published work. By citing
dynamic_topic_modeling, beyond acknowledging the work, you contribute
to make it more visible and guarantee its growing and sustainability.
For citation, please use the BibTex or the citation content.Code of ConductPlease note that thedynamic_topic_modelingproject is released with aContributor Code of
Conduct.By
contributing to this project, you agree to abide by its terms.LicenseApache License cJiaxiang Li;Shuyi Wang;Svitlana
GaleshchukBlei, David M., and John D. Lafferty. 2006. "Dynamic Topic Models." InMachine 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. GitHub. 2018.https://github.com/wshuyi/wei_lda_debate.