Python Social Media Analytics Python Social Media Analytics

Python Social Media Analytics

    • $39.99
    • $39.99

Publisher Description

Leverage the power of Python to collect, process, and mine deep insights from social media data

About This Book
Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and moreAnalyze and extract actionable insights from your social data using various Python toolsA highly practical guide to conducting efficient social media analytics at scale
Who This Book Is For

If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process.

What You Will Learn
Understand the basics of social media miningUse PyMongo to clean, store, and access data in MongoDBUnderstand user reactions and emotion detection on FacebookPerform Twitter sentiment analysis and entity recognition using PythonAnalyze video and campaign performance on YouTubeMine popular trends on GitHub and predict the next big technologyExtract conversational topics on public internet forumsAnalyze user interests on PinterestPerform large-scale social media analytics on the cloud
In Detail

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.

Style and approach

This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

GENRE
Computers & Internet
RELEASED
2017
July 28
LANGUAGE
EN
English
LENGTH
312
Pages
PUBLISHER
Packt Publishing
SELLER
PublishDrive Inc.
SIZE
29.3
MB

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