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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

Mining local businesses on Yelp

Yelp is an online service that hosts crowd-sourced reviews about local businesses, such as bars and restaurants (https://www.yelp.com). Visited by 135 million monthly users, its content is mainly community-driven.

Yelp offers three APIs that can be used to search for and interact with data about local businesses. The three APIs are grouped depending on their purpose. The search API is the entry point for keyword-based search. The business API is used to look for information about a specific business. The phone search API is used to search for a business by phone number.

The Yelp API has the rate limit of 25,000 calls per day.

This section describes the basic steps to set up an application that searches the Yelp database for particular keywords.

The access to the APIs is protected by tokens. The first step to access any of the APIs, after registering an account on Yelp, is to obtain the tokens on the developers' website (https://www.yelp.com/developers). Figure...

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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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