Details

Autor(en) / Beteiligte

• Chatterjee, Siddhartha
• Krystyanczuk, Michal

Titel

Python social media analytics : analyze and visualize data from Twitter, YouTube, GitHub, and more

Ort / Verlag

Birmingham : Packt

Erscheinungsjahr

July 2017

Verknüpfte Titel

Beschreibungen/Notizen

• 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 more * Analyze and extract actionable insights from your social data using various Python tools * A 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 mining * Use PyMongo to clean, store, and access data in MongoDB * Understand user reactions and emotion detection on Facebook * Perform Twitter sentiment analysis and entity recognition using Python * Analyze video and campaign performance on YouTube * Mine popular trends on GitHub and predict the next big technology * Extract conversational topics on public internet forums * Analyze user interests on Pinterest * Perform 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 show you why it is important.^
• 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. You will also perform web scraping and visualize data using various tools such as plotly and matplotlib. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark.