https://github.com/sampottinger/news_flower
Processing-based visualization of news sentiment across various news sources.
https://github.com/sampottinger/news_flower
news processing sentiment-analysis visualization
Last synced: 8 months ago
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Processing-based visualization of news sentiment across various news sources.
- Host: GitHub
- URL: https://github.com/sampottinger/news_flower
- Owner: sampottinger
- License: mit
- Created: 2019-08-24T00:21:08.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-08-24T00:21:35.000Z (almost 7 years ago)
- Last Synced: 2025-01-13T21:43:56.743Z (over 1 year ago)
- Topics: news, processing, sentiment-analysis, visualization
- Language: Processing
- Size: 2.23 MB
- Stars: 4
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- Changelog: news_flower.pde
- License: LICENSE.md
Awesome Lists containing this project
README
News Flower
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Visualization of news sentiment across various news sources.
Purpose
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Visualization in the form of a flower that describes the volume and sentiment polarity of articles published by different news sources. This allows users to understand which sources not only publish more work within a time period but if that work has high, low, or neutral sentiment polarity. Uses [who-wrote-this-news-crawler](https://github.com/datadrivenempathy/who-wrote-this-news-crawler). See that project for more information about the data itself.
Local Development Environment
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Visualization requires this project requires use of the [Sam Pottinger Processing](https://github.com/sampottinger/processing) branch and installation instructions are provided at that branch's README. In order to run the python data analysis steps, one will need [Jupyter](https://jupyter.org/), [Pandas](https://pandas.pydata.org/), [Matplotlib](https://matplotlib.org/), and [TextBlob](https://textblob.readthedocs.io/en/dev/). Users looking for a shortcut may consider installing [Anaconda](https://www.anaconda.com/distribution/).
Execution
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One can execute the Jupyter notebooks by running jupyter notebook within the data directory. To execute the visualization, simply open this repository within Processing and run.
Deployment
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Though the visualization will display live when the sketch is run locally, the result can be "deployed" through the `news_flower.png` file which is generated from the sketch.
Structure
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Note that the Processing sketch contents live at the root of this directory. Data preparation, artifacts, and logic for statistical tests lives under the data directory.
Coding Standards
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Please try to include JavaDoc where possible and commenting within the Jupyter notebooks as appropriate.
Open Source Libraries Used
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This project uses the following:
- [Matplotlib](https://matplotlib.org/) under the [PSF license](https://docs.python.org/3/license.html).
- [Pandas](https://pandas.pydata.org/) under the [BSD 3 Clause license](https://pandas.pydata.org/pandas-docs/stable/getting_started/overview.html#license).
- [Processing core](https://processing.org) under the [LGPL license](https://github.com/processing/processing/blob/master/license.txt).
- [TextBlob](https://textblob.readthedocs.io/en/dev/) under the [MIT license](https://github.com/sloria/TextBlob/blob/dev/LICENSE).
- [who-wrote-this-news-crawler](https://github.com/datadrivenempathy/who-wrote-this-news-crawler) under the [MIT license](https://github.com/datadrivenempathy/who-wrote-this-news-crawler/blob/master/LICENSE.md).
This project also uses colors selected via [ColorBrewer 2](https://colorbrewer2.org) and uses the [Lato free fonts](http://www.latofonts.com/lato-free-fonts/) under the [SIL license](https://scripts.sil.org/cms/scripts/page.php?item_id=OFL_web).