Science Score: 41.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 5 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.0%) to scientific vocabulary
Keywords
dynamic-topic-modeling
lda
Last synced: 6 months ago
·
JSON representation
·
Repository
dynamic topic modeling
Basic Info
- Host: GitHub
- Owner: JiaxiangBU
- License: other
- Language: Jupyter Notebook
- Default Branch: master
- Homepage: https://jiaxiangbu.github.io/dynamic_topic_modeling/
- Size: 4.62 MB
Statistics
- Stars: 40
- Watchers: 2
- Forks: 1
- Open Issues: 0
- Releases: 0
Topics
dynamic-topic-modeling
lda
Created about 6 years ago
· Last pushed about 3 years ago
Metadata Files
Readme
License
Citation
README.Rmd
---
output: github_document
bibliography: [../learn_nlp/refs/add.bib,refs/add.bib]
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# dynamic_topic_modeling
[](https://badge.fury.io/py/dynamic-topic-modeling)
[](https://zenodo.org/badge/latestdoi/238671296)
Dynamic Topic Modeling (DTM)[@Blei2006Dynamic] 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](https://github.com/wshuyi/wei_lda_debate) and [gensim](https://github.com/GSukr/dtmvisual)[@Shuyi_Wang2018;@Svitlana_2019] for Dynamic Topic Modeling.
To get started, follow the tutorials on our [Jupyter notebooks](https://nbviewer.jupyter.org/github/JiaxiangBU/dynamic_topic_modeling/tree/master/):
1. [LDA based on sklearn](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/sklearn-lda.ipynb)
2. [LDA based on gensim](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/gensim-lda.ipynb)
3. [Dynamic Topic Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/dtm.ipynb)
4. [Data Analysis on Demi Gods and Semi Devils using Dynamic Topic Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/demo.ipynb)
## 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}
}
```
`r add2pkg::add_disclaimer("Jiaxiang Li;Shuyi Wang;Svitlana Galeshchuk", license_name = "Apache License")`
Owner
- Name: Jiaxiang Li
- Login: JiaxiangBU
- Kind: user
- Location: Shanghai, China
- Website: https://jiaxiangli.netlify.com/
- Repositories: 8
- Profile: https://github.com/JiaxiangBU
李家翔 | Reviewer of XGBoost | Commiter of workflowr,tidypredict | R package developer | R, Python, Hive user | Modeler to launch solutions into production
Citation (CITATION.bib)
@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}
}
GitHub Events
Total
- Watch event: 2
Last Year
- Watch event: 2
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 43
- Total Committers: 2
- Avg Commits per committer: 21.5
- Development Distribution Score (DDS): 0.023
Top Committers
| Name | Commits | |
|---|---|---|
| Jiaxiang Li | a****g@f****m | 42 |
| dependabot[bot] | 4****]@u****m | 1 |
Committer Domains (Top 20 + Academic)
foxmail.com: 1
Issues and Pull Requests
Last synced: 8 months ago
All Time
- Total issues: 0
- Total pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: about 1 hour
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 1
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
- dependabot[bot] (1)
Top Labels
Issue Labels
Pull Request Labels
dependencies (1)
Packages
- Total packages: 1
-
Total downloads:
- pypi 31 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 4
- Total maintainers: 1
pypi.org: dynamic-topic-modeling
Run dynamic topic modeling
- Homepage: https://github.com/JiaxiangBU/dynamic_topic_modeling
- Documentation: https://dynamic-topic-modeling.readthedocs.io/
- License: Apache Software License 2.0
-
Latest release: 1.1.0
published about 6 years ago
Rankings
Dependent packages count: 10.0%
Stargazers count: 10.8%
Average: 17.6%
Dependent repos count: 21.8%
Forks count: 22.7%
Downloads: 23.0%
Maintainers (1)
Last synced:
6 months ago
Dependencies
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