Read Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data

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

4.9/5 (15411 ratings)

Description:The book offers concepts, tools, tutorials, and case studies that business managers need to extract and analyze the seven layers of social media data, including text, actions, networks, apps, hyperlinks, search engines, and location layers. Social media analytics is about converting unstructured social media data into meaningful business insights. By the end of this book, you will have mastered the concepts, techniques, and tools used to extract business insights from social media that help increase brand loyalty, generate leads, drive traffic, and ultimately make good business decisions. Here is how the book is structured. Chapter 1: this chapter sets the theme for rest of the book and introduces seven layers of social media analytics, discusses the typical steps needed to carry out the analytics, challenges and tools of social media analytics are discussed. Chapter 2: Chapter 2 briefly discusses fundamental social media technologies, their properties, and main stream social media tools, including, blogs, wikis, social network sites, content communities, and folksonomies. Chapter 3: This chapter is dedicated to Text Analytics, the first layer of social media analytics. A variety of textual elements of social media is discussed along with the steps needed to carry out text analytics, its purpose, and the tools of text analytics. The chapter also includes a step-by-step guide on analyzing social media text (e.g., tweets and comments) using Semantria for Excel. Chapter 4: Chapter 4 deals with network analytics and seeks to identify influential nodes (e.g., people and organizations) and their position in the network. Social media networks, for example, Facebook friendship network and Twitter Follower network, and YouTube commenter’s networks are discussed. The chapter also includes a case study and a step-by-step tutorial on NodeXL for analyzing social media networks. Chapter 5: Chapter 5 decomposes the second layer of social media analytics i.e., the Action Analytics. The chapter explains extracting, analyzing, and interpreting the action performed by social media users such as, likes, dislikes, shares, mentions, and endorsement. The chapter also includes a case and a step-by-step tutorial on Hootsuite analytical tool is provided. Chapter 6: Chapters 6 deals with mobile analytics issues. A practical tutorial on analyzing and understanding in-app purchases, customer engagement, and demographics are included in the chapter. A practical tutorial on Countly apps analytics tool and a real world case study is also included as part of the chapter. Chapter 7: Hyperlinks analytics is discussed in chapter 7. Social media traffic is carried out through the hyperlinks embedded within it, thus hyperlink analysis (e.g., in-links and out-links) can reveal, for example, internet traffic patterns and sources of the incoming or outgoing traffic to and from a source. A real world case study and step-by-step guidelines on hyperlinks analytics using VOSON is also included. Chapter 8: Chapter 8 outlines tools and techniques to mine and map the location of social media users, contents, and data. A real world case on mining mobile phone data and a step-by-step guide on geo-mapping your tabular business data using Google Fusion Table is also provided. Chapter 9: This chapter focus on research engine analytics including trends analysis, keyword monitoring, and advertisement spending statistics. Practical step-by-step guidelines are provided using Google Trends to analyze search engine data. Chapter 10: Chapter 10 discusses strategies and techniques to aligned social media analytics with business goals. Social media risks management is also discussed.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data. To get started finding Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 216

Format: PDF, EPUB & Kindle Edition

Publisher: CreateSpace Independent Publishing Platform

Release: 2015

ISBN

Description: The book offers concepts, tools, tutorials, and case studies that business managers need to extract and analyze the seven layers of social media data, including text, actions, networks, apps, hyperlinks, search engines, and location layers. Social media analytics is about converting unstructured social media data into meaningful business insights. By the end of this book, you will have mastered the concepts, techniques, and tools used to extract business insights from social media that help increase brand loyalty, generate leads, drive traffic, and ultimately make good business decisions. Here is how the book is structured. Chapter 1: this chapter sets the theme for rest of the book and introduces seven layers of social media analytics, discusses the typical steps needed to carry out the analytics, challenges and tools of social media analytics are discussed. Chapter 2: Chapter 2 briefly discusses fundamental social media technologies, their properties, and main stream social media tools, including, blogs, wikis, social network sites, content communities, and folksonomies. Chapter 3: This chapter is dedicated to Text Analytics, the first layer of social media analytics. A variety of textual elements of social media is discussed along with the steps needed to carry out text analytics, its purpose, and the tools of text analytics. The chapter also includes a step-by-step guide on analyzing social media text (e.g., tweets and comments) using Semantria for Excel. Chapter 4: Chapter 4 deals with network analytics and seeks to identify influential nodes (e.g., people and organizations) and their position in the network. Social media networks, for example, Facebook friendship network and Twitter Follower network, and YouTube commenter’s networks are discussed. The chapter also includes a case study and a step-by-step tutorial on NodeXL for analyzing social media networks. Chapter 5: Chapter 5 decomposes the second layer of social media analytics i.e., the Action Analytics. The chapter explains extracting, analyzing, and interpreting the action performed by social media users such as, likes, dislikes, shares, mentions, and endorsement. The chapter also includes a case and a step-by-step tutorial on Hootsuite analytical tool is provided. Chapter 6: Chapters 6 deals with mobile analytics issues. A practical tutorial on analyzing and understanding in-app purchases, customer engagement, and demographics are included in the chapter. A practical tutorial on Countly apps analytics tool and a real world case study is also included as part of the chapter. Chapter 7: Hyperlinks analytics is discussed in chapter 7. Social media traffic is carried out through the hyperlinks embedded within it, thus hyperlink analysis (e.g., in-links and out-links) can reveal, for example, internet traffic patterns and sources of the incoming or outgoing traffic to and from a source. A real world case study and step-by-step guidelines on hyperlinks analytics using VOSON is also included. Chapter 8: Chapter 8 outlines tools and techniques to mine and map the location of social media users, contents, and data. A real world case on mining mobile phone data and a step-by-step guide on geo-mapping your tabular business data using Google Fusion Table is also provided. Chapter 9: This chapter focus on research engine analytics including trends analysis, keyword monitoring, and advertisement spending statistics. Practical step-by-step guidelines are provided using Google Trends to analyze search engine data. Chapter 10: Chapter 10 discusses strategies and techniques to aligned social media analytics with business goals. Social media risks management is also discussed.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data. To get started finding Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data

Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data

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