Book Image

Python Social Media Analytics

By : Baihaqi Siregar, Siddhartha Chatterjee, Michal Krystyanczuk
Book Image

Python Social Media Analytics

By: Baihaqi Siregar, Siddhartha Chatterjee, Michal Krystyanczuk

Overview of this book

Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.
Table of Contents (17 chapters)
Title Page
About the Authors
About the Reviewer
Customer Feedback

MongoDB using Python

MongoDB can be used directly from the shell command or through programming languages. For the sake of our book we'll explain how it works using Python. MongoDB is accessed using Python through a driver module named PyMongo.


We will not go into the detailed usage of MongoDB, which is beyond the scope of this book. We will see the most common functionalities required for analysis projects. We highly recommend reading the official MongoDB documentation.

PyMongo can be installed using the following command:

pip install pymongo

Then the following command imports it in the Python script

from pymongo import MongoClient 
client = MongoClient('localhost:27017') 

The database structure of MongoDB is similar to SQL languages, where you have databases, and inside databases you have tables. In MongoDB you have databases, and inside them you have collections. Collections are where you store the data, and databases store multiple collections. As MongoDB is a NoSQL database, your tables...