Graph Databases
Applications on Social Media Analytics and Smart Cities
- 180 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
With social media producing such huge amounts of data, the importance of gathering this rich data, often called "the digital gold rush", processing it and retrieving information is vital. This practical book combines various state-of-the-art tools, technologies and techniques to help us understand Social Media Analytics, Data Mining and Graph Databases, and how to better utilize their potential.
Graph Databases: Applications on Social Media Analytics and Smart Cities reviews social media analytics with examples using real-world data. It describes data mining tools for optimal information retrieval; how to crawl and mine data from Twitter; and the advantages of Graph Databases. The book is meant for students, academicians, developers and simple general users involved with Data Science and Graph Databases to understand the notions, concepts, techniques, and tools necessary to extract data from social media, which will aid in better information retrieval, management and prediction.
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Preface
- Contents
- Introduction
- 1 From Relational to NoSQL Databases – Comparison and Popularity Graph Databases and the Neo4j Use Cases
- 2 A Comparative Survey of Graph Databases and Software for Social Network Analytics: The Link Prediction Perspective
- 3 A Survey on Neo4j Use Cases in Social Media: Exposing New Capabilities for Knowledge Extraction
- 4 Combining and Working with Multiple Social Networks on a Single Graph
- 5 Child Influencers on YouTube: From Collection to Overlapping Community Detection
- 6 Managing Smart City Linked Data with Graph Databases: An Integrative Literature Review
- 7 Graph Databases in Smart City Applications – Using Neo4j and Machine Learning for Energy Load Forecasting 7
- 8 A Graph-Based Data Model for Digital Health Applications
- Index