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Mastering Social Media Mining with Python

You're reading from Mastering Social Media Mining with Python Unearth deeper insight from your social media data with advanced Python techniques for acquisition and analysis

Product type Paperback

Published in Jul 2016

Publisher Packt

ISBN-13 9781783552016

Length 338 pages

Edition 1st Edition

Languages

Python

Concepts

Data Mining

Author (1):

Marco Bonzanini

View More author details

Table of Contents (10) Chapters

Preface

1. Social Media, Social Data, and Python FREE CHAPTER

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

3. Users, Followers, and Communities on Twitter

4. Posts, Pages, and User Interactions on Facebook

5. Topic Analysis on Google+

6. Questions and Answers on Stack Exchange

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

8. Mining All the Data!

9. Linked Data and the Semantic Web

Chapter 6. Questions and Answers on Stack Exchange

This chapter is about Stack Exchange, the question and answer network, and the broader topic of question answering.

In this chapter, we will discuss the following topics:

How to create an app that interacts with the Stack Exchange API
How to search for users and questions on Stack Exchange
How to deal with data dumps for offline processing
Supervised machine learning methods for text classification
How to predict question tags using machine learning
How to embed a machine learning model in a real-time application

The rest of the chapter is locked

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Authors (1)

Bonzanini

Bonzanini

Marco Bonzanini is a data scientist based in London, United Kingdom. He holds a Ph.D. in information retrieval from the Queen Mary University of London. He specializes in text analytics and search applications, and over the years, he has enjoyed working on a variety of information management and data science problems. He maintains a personal blog at https://marcobonzanini.com, where he discusses different technical topics, mainly around Python, text analytics, and data science. When not working on Python projects, he likes to engage with the community at PyData conferences and meetups, and he also enjoys brewing homemade beer.

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