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Mastering Social Media Mining with Python

Mastering Social Media Mining with Python

By : Bonzanini
4.7 (6)
Buy this Book
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Mastering Social Media Mining with Python

Mastering Social Media Mining with Python

4.7 (6)
By: Bonzanini
Buy this Book

Overview of this book

Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights. This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Social Media, Social Data, and Python
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1. Social Media, Social Data, and Python
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Getting started
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Social media - challenges and opportunities
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Python tools for data science
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Processing data in Python
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Building complex data pipelines
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Summary
2
2. #MiningTwitter – Hashtags, Topics, and Time Series
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2. #MiningTwitter – Hashtags, Topics, and Time Series
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Getting started
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The Twitter API
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Collecting data from Twitter
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Analyzing tweets - entity analysis
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Analyzing tweets - text analysis
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Analyzing tweets - time series analysis
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Summary
3
3. Users, Followers, and Communities on Twitter
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3. Users, Followers, and Communities on Twitter
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Users, friends, and followers
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Mining your followers
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Mining the conversation
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Plotting tweets on a map
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Summary
4
4. Posts, Pages, and User Interactions on Facebook
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4. Posts, Pages, and User Interactions on Facebook
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The Facebook Graph API
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Mining your posts
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Mining Facebook Pages
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Summary
5
5. Topic Analysis on Google+
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5. Topic Analysis on Google+
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Getting started with the Google+ API
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Embedding the search results in a web GUI
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Notes and activities from a Google+ page
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Text analysis and TF-IDF on notes
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Summary
6
6. Questions and Answers on Stack Exchange
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6. Questions and Answers on Stack Exchange
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Questions and answers
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Getting started with the Stack Exchange API
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Working with Stack Exchange data dumps
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Text classification for question tags
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Summary
7
7. Blogs, RSS, Wikipedia, and Natural Language Processing
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7. Blogs, RSS, Wikipedia, and Natural Language Processing
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Blogs and NLP
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Getting data from blogs and websites
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NLP Basics
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Summary
8
8. Mining All the Data!
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8. Mining All the Data!
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Many social APIs
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Mining videos on YouTube
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Mining open source software on GitHub
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Mining local businesses on Yelp
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Building a custom Python client
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Summary
9
9. Linked Data and the Semantic Web
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9. Linked Data and the Semantic Web
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A Web of Data
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Mining relations from DBpedia
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Mining geo coordinates
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Summary

Mining relations from DBpedia

DBpedia is one of the best-known sources of Linked Data. Based on Wikipedia, it augments the content of the popular wiki-based encyclopedia with semantic connections between entities. The structured information from DBpedia can be accessed via the Web using a SQL-like language called SPARQL, a semantic query language for RDF.

In Python, while we have the option of querying the database with SPARQL, we can take advantage of the RDFLib package, a library used to work with RDF.

From our virtual environment, we can install it using pip:

$ pip install rdflib

Given the complexity of the Semantic Web topic, we prefer to dig into an example so that you can have the flavor of the capabilities of DBpedia, and at the same time, get an overview of how to use the RDFLib package.

The rdf_summarize_entity.py script looks up for a given entity and tries to output its summary to the user:

# Chap09/rdf_summarize_entity.py 
from argparse import ArgumentParser 
import rdflib...
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Mastering Social Media Mining with Python
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