Metadata-Version: 2.1
Name: TTLocVis
Version: 0.1.0
Summary: TTLocVis: A Twitter Topic Location Visualization package
Home-page: https://github.com/xillig/TTLocVis
Author: Gillian Kant, Christoph Weisser, Benjamin Saefken
Author-email: gilliankant@googlemail.com, c.weisser@stud.uni-goettingen.de, benjamin.saefken@uni-goettingen.de
Maintainer: Gillian Kant
Maintainer-email: gilliankant@googlemail.com
License: GNU GPLv3
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pip (>=19.1.1)
Requires-Dist: gensim (>=3.8.1)
Requires-Dist: matplotlib (>=2.2.2)
Requires-Dist: numpy (==1.16.1)
Requires-Dist: pandas (==0.24.2)
Requires-Dist: pyproj (>=2.6.1.post1)
Requires-Dist: scikit-learn (>=0.21.2)
Requires-Dist: spacy (>=2.2.2)
Requires-Dist: tweepy (>=3.8.0)
Requires-Dist: urllib3 (>=1.25.8)
Requires-Dist: wordcloud (>=1.7.0)


# TTLocVis

A Twitter Topic Location Visualization Python package

## Summary   

The package TTLocVis provides a broad range of methods to generate, clean, analyze and visualize the content of Twitter data.
TTLocVis enables the user to work with geo-spatial Twitter data and to generate topic distributions from LDA Topic Models
for geo-coded Tweets. As such, TTLocVis is an innovative tool to work with geo-coded text on a high geo-spatial resolution to 
analyse the public discourse on various topics in space and time. The package has the potential to be used for a broad range of applications 
for scientific research to gain insights into public discourse.

## How to cite 

#Installation

__Attention:__ Event though TTLocVis should run on Python 3.7 and 3.8, it was not fully tested under these conditions.
We do recommend to install a new (conda) environment with Python 3.6. 

The package can be installed via *pip*:
```commandline
python pip install TTLocVis
```

####Windows

After successful installation, the user must download the [*basemap* package] and install it manually via *pip*:
```commandline
python -m pip install [path-to-the-downloaded-file/your-basemap-wheel]
```
__Note:__ Do not copy the name of your *basemap wheel* from the above mentioned website into your python console! Write
it out manually!
The *cpXX* in the filenames refer to the python version you will use. An example for Python 3.6. would be the file 
*basemap-1.2.1-cp36-cp36m-win_amd64.whl* Remember, TTLocVis is developed to run only on Python 3.6, 3.7 and 3.8.

[*basemap* package]: https://www.lfd.uci.edu/~gohlke/pythonlibs/#basemap

####Linux and iOS

Download [basemap package version 1.2.1] and install it accordingly.

[basemap package version 1.2.1]: https://github.com/matplotlib/basemap/releases

## Documentation and Usage

You can find the current TTLocVis master branch
documentation at our [documentation website].

[documentation website]: https://ttlocvis.readthedocs.io/en/latest/

## Community guidelines

Contributions to TTLocVis are welcome.

- Just file an Issue to ask questions, report bugs, or request new features.
- Pull requests via GitHub are also welcome.

Potential contributions include ways to further improve the quality of the LDA topics in handling the noisy
Twitter data and an improvement of the *loc_vis* method in a way that it becomes independent form the *basemap*
module.

## Authors

- Gillian Kant
- Christoph WeiÃŸer
- Benjamin SÃ¤fken

## License

TTLocVis is published under the __GNU GPLv3__ license.

