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FacebookPostsAnalysis

FacebookPostsAnalysis (MI-PYT@FIT CTU semestral work) is a Python 3.6 application to analyze the posts of a Facebook page or open group - total number of reactions, most liked posts, activity of users, and much more. All of the posts are exported into a .csv file, which can be opened with your preferred spreadsheet software, and then automatically analyzed using Jupyter Notebook.

To see the example .csv file / notebook, please see the examples folder, containing analysis of Python Developers Facebook group.


Installation

There are two ways how to install FacebookPostsAnalysis:

  1. Installation directly from TestPyPI, using the following command:

python -m pip install --extra-index-url https://test.pypi.org/pypi FacebookPostsAnalysis

  1. If any problem occurred, please follow these steps:
  • Download FacebookPostsAnalysis directly from TestPyPI here.
  • Unpack the download .tar.gz file.
  • Use the following command in the labelord directory: python setup.py install

Please note that FacebookPostsAnalysis requires at least Python 3.6 to be installed to run properly!

Usage

In order to successfully cooperate with Facebook Graph API, every user has to register and configure his own App, which is bounded with APP ID and APP SECRET. For FacebookPostsAnalysis to work properly, you need to specify these in the configuration file (see config.cfg), along with the ID of Facebook open page/group you want to analyze.

After proper specification of your credentials and Facebook open page/group ID in configuration file, you are ready to use FacebookPostsAnalysis. Application uses command line interface for its functionality:

analysis get_posts [OPTIONS] [ENTITY]

You can use the following options to specify the desired time period/range:

--until: Date until when to analyse Facebook posts.

--since: Date since when to analyse Facebook posts.

--year: Year to analyse Facebook posts.

The ENTITY argument is also required. You can choose from two ENTITY arguments: page or group (depends on which you want to analyze).

For more information about the usage of FacebookPostsAnalysis, please see the documentation.

Documentation

For the full documentation, please visit Readthedocs.io.

You can also build the documentation locally. Just follow these steps:

  1. Download FacebookPostsAnalysis and install it (in the main directory: python setup.py install)
  2. Navigate to docs directory
  3. Run python -m pip install -r requirements.txt
  4. Run make html
  5. You can find all of the .html files in _build/html directory

License

This project is licensed under the MIT License.

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