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Python social media analytics : analyze and visualize data from Twitter, YouTube, GitHub, and more /
Leverage the power of Python to collect, process, and mine deep insights from social media dataAbout This Book* Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more* Analyze and extract actionable insights from your social data using various Python to...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2017.
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Authors; Acknowledgments; About the Reviewer; www.PacktPub.com; Customer Feedback; Table of Contents; Preface; Chapter 1: Introduction to the Latest Social Media Landscape and Importance; Introducing social graph; Notion of influence; Social impacts; Platforms on platform; Delving into social data; Understanding semantics; Defining the semantic web; Exploring social data applications; Understanding the process; Working environment; Defining Python; Selecting an IDE; Illustrating Git; Getting the data; Defining API; Scraping and crawling; Analyzing the data.
- Brief introduction to machine learningTechniques for social media analysis; Setting up data structure libraries; Visualizing the data; Getting started with the toolset; Summary; Chapter 2: Harnessing Social Data
- Connecting, Capturing, and Cleaning; APIs in a nutshell; Different types of API; RESTful API; Stream API; Advantages of social media APIs; Limitations of social media APIs; Connecting principles of APIs; Introduction to authentication techniques; What is OAuth?; User authentication; Application authentication; Why do we need to use OAuth?
- Connecting to social network platforms without OAuthOAuth1 and OAuth2; Practical usage of OAuth; Parsing API outputs; Twitter; Creating application; Selecting the endpoint; Using requests to connect; Facebook; Creating an app and getting an access token; Selecting the endpoint; Connect to the API; GitHub; Obtaining OAuth tokens programmatically; Selecting the endpoint; Connecting to the API; YouTube; Creating an application and obtaining an access token programmatically; Selecting the endpoint; Connecting to the API; Pinterest; Creating an application; Selecting the endpoint.
- Connecting to the APIBasic cleaning techniques; Data type and encoding; Structure of data; Pre-processing and text normalization; Duplicate removal; MongoDB to store and access social data; Installing MongoDB; Setting up the environment; Starting MongoDB; MongoDB using Python; Summary; Chapter 3: Uncovering Brand Activity, Popularity, and Emotions on Facebook; Facebook brand page; The Facebook API; Project planning; Scope and process; Data type; Analysis; Step 1
- data extraction; Step 2
- data pull; Step 3
- feature extraction; Step 4
- content analysis; Keywords.
- Extracting verbatims for keywordsUser keywords; Brand posts; User hashtags; Noun phrases; Brand posts; User comments; Detecting trends in time series; Maximum shares; Brand posts; User comments; Maximum likes; Brand posts; Comments; Uncovering emotions; How to extract emotions?; Introducing the Alchemy API; Connecting to the Alchemy API; Setting up an application; Applying Alchemy API; How can brands benefit from it?; Summary; Chapter 4: Analyzing Twitter Using Sentiment Analysis and Entity Recognition; Scope and process; Getting the data; Getting Twitter API keys; Data extraction.