Social media contains different types of data: information about user profiles, statistics (number of likes or number of followers), verbatims, and media. Quantitative data is very convenient for an analysis using statistical and numerical methods, but unstructured data such as user comments is much more challenging. To get meaningful information, one has to perform the whole process of information retrieval. It starts with the definition of the data type and data structure. On social media, unstructured data is related to text, images, videos, and sound and we will mostly deal with textual data. Then, the data has to be cleaned and normalized. Only after all these steps can we delve into the analysis.
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Python Social Media Analytics
By :
Python Social Media Analytics
By:
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 (10 chapters)
Preface
Free Chapter
Introduction to the Latest Social Media Landscape and Importance
Harnessing Social Data - Connecting, Capturing, and Cleaning
Uncovering Brand Activity, Popularity, and Emotions on Facebook
Analyzing Twitter Using Sentiment Analysis and Entity Recognition
Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured
The Next Great Technology – Trends Mining on GitHub
Scraping and Extracting Conversational Topics on Internet Forums
Demystifying Pinterest through Network Analysis of Users Interests
Social Data Analytics at Scale – Spark and Amazon Web Services
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