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Social Media Mining

An Introduction

by Reza Zafarani, Mohammad Ali Abbasi, Huan Liu

Social Media Mining

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Book Description

The growth of social media over the last decade has revolutionized the way individuals interact and industries conduct business. Individuals produce data at an unprecedented rate by interacting, sharing, and consuming content through social media. Understanding and processing this new type of data to glean actionable patterns presents challenges and opportunities for interdisciplinary research, novel algorithms, and tool development. Social Media Mining integrates social media, social network analysis, and data mining to provide a convenient and coherent platform for students, practitioners, researchers, and project managers to understand the basics and potentials of social media mining. It introduces the unique problems arising from social media data and presents fundamental concepts, emerging issues, and effective algorithms for network analysis and data mining. Suitable for use in advanced undergraduate and beginning graduate courses as well as professional short courses, the text contains exercises of different degrees of difficulty that improve understanding and help apply concepts, principles, and methods in various scenarios of social media mining.

This open book is licensed under a Open Publication License (OPL). You can download Social Media Mining ebook for free in PDF format (5.0 MB).

Table of Contents

Chapter 1
Introduction
Part I
Essentials
Chapter 2
Graph Essentials
Chapter 3
Network Measures
Chapter 4
Network Models
Chapter 5
Data Mining Essentials
Part II
Communities and Interactions
Chapter 6
Community Analysis
Chapter 7
Information Diffusion in SocialMedia
Part III
Applications
Chapter 8
Influence and Homophily
Chapter 9
Recommendation in Social Media
Chapter 10
Behavior Analytics

Book Details

Title
Social Media Mining
Subject
Computer Science
Publisher
Cambridge University Press
Published
2014
Pages
382
Edition
1
Language
English
ISBN13 Digital
9781107018853
ISBN10 Digital
1107018854
PDF Size
5.0 MB
License
Open Publication License

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