Mastering Social Media Mining with Python电子书

Mastering Social Media Mining with Python

Mastering Social Media Mining with Python

Credits

About the Author

About the Reviewer

www.PacktPub.com

eBooks, discount offers, and more

Why subscribe?

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Social Media, Social Data, and Python

Getting started

Social media - challenges and opportunities

Opportunities

Challenges

Social media mining techniques

Python tools for data science

Python development environment setup

pip and virtualenv

Conda, Anaconda, and Miniconda

Efficient data analysis

Machine learning

Natural language processing

Social network analysis

Data visualization

Processing data in Python

Building complex data pipelines

Summary

2. #MiningTwitter – Hashtags, Topics, and Time Series

Getting started

The Twitter API

Rate limits

Search versus Stream

Collecting data from Twitter

Getting tweets from the timeline

The structure of a tweet

Using the Streaming API

Analyzing tweets - entity analysis

Analyzing tweets - text analysis

Analyzing tweets - time series analysis

Summary

3. Users, Followers, and Communities on Twitter

Users, friends, and followers

Back to the Twitter API

The structure of a user profile

Downloading your friends' and followers' profiles

Analysing your network

Measuring influence and engagement

Mining your followers

Mining the conversation

Plotting tweets on a map

From tweets to GeoJSON

Easy maps with Folium

Summary

4. Posts, Pages, and User Interactions on Facebook

The Facebook Graph API

Registering your app

Authentication and security

Accessing the Facebook Graph API with Python

Mining your posts

The structure of a post

Time frequency analysis

Mining Facebook Pages

Getting posts from a Page

Facebook Reactions and the Graph API 2.6

Measuring engagement

Visualizing posts as a word cloud

Summary

5. Topic Analysis on Google+

Getting started with the Google+ API

Searching on Google+

Embedding the search results in a web GUI

Decorators in Python

Flask routes and templates

Notes and activities from a Google+ page

Text analysis and TF-IDF on notes

Capturing phrases with n-grams

Summary

6. Questions and Answers on Stack Exchange

Questions and answers

Getting started with the Stack Exchange API

Searching for tagged questions

Searching for a user

Working with Stack Exchange data dumps

Text classification for question tags

Supervised learning and text classification

Classification algorithms

Naive Bayes

k-Nearest Neighbor

Support Vector Machines

Evaluation

Performing text classification on Stack Exchange data

Embedding the classifier in a real-time application

Summary

7. Blogs, RSS, Wikipedia, and Natural Language Processing

Blogs and NLP

Getting data from blogs and websites

Using the WordPress.com API

Using the Blogger API

Parsing RSS and Atom feeds

Getting data from Wikipedia

A few words about web scraping

NLP Basics

Text preprocessing

Sentence boundary detection

Word tokenization

Part-of-speech tagging

Word normalization

Case normalization

Stemming

Lemmatization

Stop word removal

Synonym mapping

Information extraction

Summary

8. Mining All the Data!

Many social APIs

Mining videos on YouTube

Mining open source software on GitHub

Mining local businesses on Yelp

Building a custom Python client

HTTP made simple

Summary

9. Linked Data and the Semantic Web

A Web of Data

Semantic Web vocabulary

Microformats

Linked Data and Open Data

Resource Description Framework

JSON-LD

Schema.org

Mining relations from DBpedia

Mining geo coordinates

Extracting geodata from Wikipedia

Plotting geodata on Google Maps

Summary