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SEVEN LAYERS OF SOCIAL MEDIA ANALYTICS
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SEVEN LAYERS OF SOCIAL MEDIA ANALYTICS

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SEVEN LAYERS OF SOCIAL

MEDIA ANALYTICS

SEVEN LAYERS OF SOCIAL

MEDIA ANALYTICS

Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search

Engine, and Location Data

Gohar F. Khan

Copyright © 2015 Gohar F. Khan

All rights reserved.

ISBN: 1507823207

ISBN-13: 9781507823200

“This is a useful guide to the emerging world of social media analysis. It offers

one the first practical frameworks for understanding social media. The volume

provides step-by-step instructions for the complete work flow for data collection

and analysis, including advanced network science methods. This is a must read

for serious analysts seeking to empirically document and optimize social

media.”—Marc Smith, Director, Social Media Research Foundation.

“the seven layers of social media analytics explores the value of analyzing social

media data for informing organizational decision making. It provides a 7-step

process that is straightforward, showing a way out of the dense and murky

impressions from a huge collection of status updates, comments, hyperlinks and

other online verbal jungle.”—Gabrielle Iglesias, Knowledge Management &

Communication Specialist, Asian Disaster Preparedness Center.

“Although we are still living in the early years of the digital network revolution,

some of its consequences for politics, economics, society and business are

already apparent. One of these is the dramatic rise in recent years of social media

which, along with the burgeoning Internet of things, are themselves a major

source of so-called “big data.” For companies, individuals and organizations

seeking to find their way in the new communications environment, Gohar F.

Khan has provided a very helpful guidebook to the use of social media analytics.

It is well organized and clearly written and should help many make sense of this

rapidly emerging, increasingly consumer and citizen-centric

environment.”—James F. Larson, Professor and Chair, Department of

Technology and Society, SUNY Korea.

“Seven layers of social media analytics provides a fascinating insight into how

social media data can be mined for business intelligence purposes. Given the

growing importance of social media, this book is highly recommended.”-Jacob

Wood, Assistant Professor, Korea University of Technology and Education.

To my lovely family.

Thank you. Without your support and patience, I would have never completed

this book.

The book comes with a companion site (www.7LayersAnalytics.com) which

hosts:

✓ Up-to-Date Tutorials (with screenshots)

✓ Lecture Slides

✓ Case Studies

✓ Sample Data, and

✓ Sample Syllabus.

CONTENTS

Acknowledgments

Preface

Chapter 1: Social Media A Analytics: An Overview

Purpose of Social Media Analytics

Social Media vs. Traditional Business Analytics

Seven Layers of Social Media Analytics

Layer One: Text

Layer Two: Networks

Layer Three: Actions

Layer Four: Mobile

Layer Five: Hyperlinks

Layer Six: Location

Layer Seven: Search Engines

Types of Social Media Analytics

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

Social Media Analytics Cycle

Step 1: Identification

Step 2: Extraction

Step 3: Cleaning

Step 4: Analyzing

Step 5: Visualization

Step 6: Interpretation

Challenges to Social Media Analytics

Volume and Velocity as a Challenge

Diversity as Challenge

Unstructuredness as a Challenge

Social Media Analytics Tools

Case Study: The Underground Campaign that Scored Big

Background

The Goal

The Challenge

The Solution

Influencing the Right Demographic

Underground Results

The Right Line·

Commentating to Commuters

Chapter 2: Introduction to Social Media

World Wide Web

Web 1.0

Web 2.0

Web 3.0

Social Media

Core Characteristics of Social Media

Social Media Is Many-to-Many

Social Media Is Participatory

Social Media Is User Owned

Social Media Is Conversational

Social Media Enables Openness

Social Media Enables Mass Collaboration

Social Media Is Relationship Oriented

Social Media Is Free And Easy to Use

Types of Social Media

Social Networking Sites

Using Facebook for Business Purposes

Content Communities

Using YouTube for Business Purposes

Blogs

Blog Features

Using Blogs for Business Purposes

Microblogging

Tweet

Retweet (RT)

Direct messages

Following

Followers

Mention

Hashtags (#)

Using Twitter for Business Purposes

Online Collaborative Projects

Using Wikis for Business Purposes

Folksonomies or Tagging (e.g., del.icio.us)

Virtual Worlds

Mobile Apps

Purpose-Built Platforms

Chapter 3: Social Media Text Analytics

Types of Social Media Text

Dynamic Text

Tweet

Comments

Discussion

Conversation

Reviews

Static Text

Purpose of Text Analytics

Sentiment Analysis

Intention Mining

Trends Mining

Concept Mining

Steps in Text Analytics

Identification and Searching

Text Parsing and Filtering

Text Transformation

Text Mining

Social Media Text Analysis Tools

Case Study: Tapping into Online Customer Opinions

Background

The Problem

Solution

Step 1: Data Collection & Preparation

Step 2: Text Coding & Categorization

Step 3: Text Mining, Visualization, and Interpretation

Positive/Negative comments and overlapping terms

Data patterns within different hotel brands

Longitudinal data patterns

Analysis of Poster Groups

Conclusion

Tutorial: Text Analytics with Semantria

Introduction

Getting Started

Running an Analysis

Understanding Your Analysis

Detailed Analysis

Creating a User Category

Understanding and Creating Queries

Utilizing VLookup

Building Nested Queries

Conclusion

Chapter 4: Social Media Network Analytics

Common Network Terms

Network

Social Networks

Social Network Site

Social Networking

Social Network Analysis

Common Social Media Network Types

Friendship Networks

Follow-Following Networks

Fan Network

Group Network

Professional Networks

Content Networks

Dating Networks

Coauthorship Networks

Cocommenter Networks

Colike

Cooccurrence Network

Geo Coexistence Network

Hyperlink Networks

Types of Networks

Based on Existence

Implicit Networks

Explicit Networks

Based on Direction

Directed Networks

Undirected Network

Based on Mode

One-Mode Networks

Two-Mode Networks

Multimode Network

Based on Weights

Weighted Networks

Unweighted Networks

Common Network Terminologies

Node-Level Properties

Degree Centrality

Betweenness Centrality

Eigenvector Centrality

Structural Holes

Network-Level Properties

Clustering Coefficient

Density

Components

Diameter

Average Degree

Network Analytics Tools

Case Study: Do Social Media Networks Reflect Social Culture?

Background

What They Did

Results

What We Learn from the Case Study

Tuturial: Analyzing Social Media Networks with NodeXL

Installing and Running NodeXL

Understanding NodeXL Workflow

Stage 1: Importing Network Data

Importing Third-party Data Importers

Importing a Social Media Network Directly

Stage 2: Cleaning the Network Data

Stage 3: Network Analysis

Further Adjustments

Saving the Network

Chapter 5: Social Media Actions Analytics

What Is Actions Analytics?

Common Social Media Actions

Like

Dislike

Share

Visitors, Visits, Revisits

View

Clicks

Tagging

Mentions

Hovering

Check-in

Pinning

Embeds

Endorsement

Uploading and Downloading

Actions Analytics Tools

Case Study: Cover-More Group

Visualizing the ROI of Social

Cover-More Group

What They Did

How They Did It

The Results

Tutorial: Analyzing Social Media Actions with Hootsuite

Adding Streams

Creating a tab

Scheduling a Message

Analytics with Hootsuite

Creating Custom Reports

Monitoring and Analyzing Facebook Data with Hootsuite

Adding a Facebook Stream

Chapter 6: Mobile Analytics

What Is Mobile Analytics?

Mobile Web Analytics

Apps Analytics

Purpose of Apps Analytics

Types of Apps

From the Perspective of Development

Native Apps

Web-Based Apps

Hybrid Apps

From the Perspective of Objectives

Transaction-Oriented Apps

Ads-Oriented Apps

Information-Oriented Apps

Networking-Oriented Apps

Communication-Oriented Apps

Entertainment-Oriented Apps

Education-Oriented Apps

Self-Improvement Apps

Characteristics of Mobile Apps

Always On

Moveable

Location Awareness

Focused

Personalization

Short-Term Use

Easy to Use

Developing Your Own App

Do-It-Yourself

Outsource It

Go Open Source

Mobile Analytics Tools

Case Study: Mobile Analytics to Optimize Process

About Airbnb

The problem

Solution

Outcome

Tutorial: Apps Analytics with Countly

Dashboard Overview

Navigation Bar

Real-Time Panel

Quick Date Selector

Analytics Panel

Getting In-Depth Analytics

Engagement View

Events

Funnels

Applications and Users

Revenue Analytics Panel

Changing Interface Language

Chapter 7: Social Media Hyperlink Analytics

Types of Hyperlinks

In-Links

Out-Links

Co-Links

Hyperlink Analytics

Types of Hyperlink Analytics

Hyperlink Environment Analysis

Co-Link Networks

In-Links and Out-Links Networks

Link Impact Analysis

Social Media Hyperlink Analysis

Hyperlink Analytics Tools

Case Study: Hyperlinks and Viral YouTube Videos

Background

What They Did

Results

Conclusion

Tutorial: Hyperlinks Analytics with VOSON

Create an Account

Logging in to VOSON

VOSON Menus

Info

Data

Create

Help

Creating a Hyperlink Network

Chapter 8: Location Analytics

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