Social Media Data Automating with Python

Social Media Data Automating

Introduction

The Social Media Data Automation project simplifies the process of gathering insights from popular platforms like Facebook, Twitter, and Instagram. Using Python, it automates data fetching through APIs or web scraping, allowing users to easily collect post engagement rates, likes, and other metrics. The project integrates seamlessly with Google Sheets, updating data in real-time and providing visual insights through macros. Ideal for businesses or individuals seeking efficient social media management, this tool streamlines data collection and analysis, saving time and improving decision-making through automated processes.

Overview of the Project

• Purpose: Automating the process of fetching social media data, such as engagement rates and post insights, from platforms like Facebook, Twitter, and Instagram. The data is then sent to Google Sheets for further analysis and chart updates using Google Sheets macros.
• Languages/Tools Used:
• Python 3.6.12: Main programming language used in the project.
• APIs: The project interacts with social media APIs for data fetching.
• Web Scraping: For platforms or data points where API access is limited, scraping methods are used.
• Google Sheets: The collected data is stored and analyzed in Google Sheets, with updates automated using macros.
• Scripts Included:
• FacebookDataFetch.py: Script for fetching Facebook data (likely using the Facebook Graph API).
• InstagramDataFetch.py: Script for fetching Instagram data.
• TwitterDataFetch.py: Script for fetching Twitter data (likely using the Twitter API).
• MediumStats.py: Script related to scraping data from Medium or some other content platform.
• GoogleAnalytics.py: Possibly to fetch analytics data from Google Analytics or manage Google Sheets integration.

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Key Features

1. Data Fetching: Automates the fetching of social media post insights like engagement rates, likes, shares, comments, etc.
2. Scraping: If APIs don’t provide certain data, web scraping methods are implemented.
3. Integration with Google Sheets: The fetched data is updated into Google Sheets, which allows for easy visualization and analysis.
4. Automation with Macros: Google Sheets macros are used to automatically update charts and stats based on the latest fetched data.

How to Use

1. Clone the Repository:

   git clone https://github.com/mayankpruthii/SocialMediaDataAutomation.git

2. Install Dependencies:

• Install Python 3.6.12 if you haven’t already.
• Install the required Python packages:
  bash pip install -r requirements.txt

2. Set Up Social Media APIs:

• Get API keys for Facebook, Twitter, and Instagram, and configure them in the respective scripts (FacebookDataFetch.py, InstagramDataFetch.py, TwitterDataFetch.py).

2. Run the Scripts:

• Fetch data for each platform by running the respective scripts:
  bash python FacebookDataFetch.py python InstagramDataFetch.py python TwitterDataFetch.py

2. View Data in Google Sheets:

• Once the data is fetched, it will be automatically sent to Google Sheets. Macros will update the charts for data analysis.

Potential Enhancements:

• You can expand this project by adding support for more platforms (e.g., LinkedIn, YouTube).
• Integrate additional data analytics or visualization tools such as Power BI or Tableau.
• Implement a dashboard for real-time data tracking.

Let me know if you’d like more detailed information or guidance on specific parts of this project!

Source Code

To extract a ZIP file, you can follow these step-by-step instructions depending on the operating system you’re using:

1. Download the ZIP File: Ensure the ZIP file is saved on your computer.
2. Locate the ZIP File: Open the folder where the ZIP file is saved.
3. Right-Click the ZIP File: There will be a context menu shown.
4. Click “Extract All… to begin the extraction process.
5. Choose a Destination Folder: You can either keep the default location or choose a new folder to extract the contents.

Social Media Data Automating and Analysis SOURCE CODE: CLICK THE BUTTON BELOW

• Social Media Data Automating and Analysis with Python
• Social Media Data Automating