| Description |
1 online resource (159 p.) |
| Series |
Synthesis Lectures on Information Concepts, Retrieval, and Services |
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Synthesis Lectures on Information Concepts, Retrieval, and Services (Springer (Firm))
|
| Contents |
Intro -- Foreword -- Preface -- Acknowledgements -- Contents -- About the Authors -- Acronyms -- Part I Introduction to Analytics -- 1 The Foundations of Web Analytics -- 1.1 Defining Digital Analytics -- 1.2 Realizing the Role of Web Analytics -- 1.3 Key Performance Indicators -- 2 The Foundations of Social Media Analytics -- 2.1 Definition -- 2.2 The Role of Social Media Analytics -- 2.3 Social Media Usage -- 2.4 Key Performance Indicators -- 2.5 Social Media User Engagement -- 2.6 Terminology -- 3 Web and Social Media Analytics Strategy -- 3.1 Introduction |
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3.2 The Benefits of a Strategy -- 3.3 Web Strategy -- 3.3.1 What is a Web Strategy? -- 3.3.2 Key Performance Indicators -- 3.3.3 Steps in Building a Successful Web Analytics Strategy -- 3.4 Social Media Strategy -- 3.4.1 What is a Social Media Strategy? -- 3.4.2 Key Performance Indicators -- 3.4.3 Steps in Building a Successful Social Media Strategy -- Part II Data Sources -- 4 Data Collection Methods -- 4.1 Introduction -- 4.2 Online Surveys -- 4.3 Crowdsourcing -- 4.4 Eye Tracking -- 4.5 Mouse Tracking -- 4.6 Search Logs -- 4.7 Triangulation -- 4.8 Social Media APIs |
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Part III Data Quality and Preparation -- 5 Data Quality Assessment -- 5.1 Introduction -- 5.2 Data Quality Assessment Aspects -- 5.2.1 Completeness and Consistency -- 5.2.2 Validity, Accuracy, and Timeliness -- 5.2.3 Examples of Data Quality Assessment Aspects -- 5.3 Data Quality Assessment Methods -- 5.4 Data Quality Assessment Tools -- 5.5 Data Quality Metrics -- 5.6 The Challenges of Data Quality Assessment -- 5.6.1 Examples of Challenges in Data Quality Assessment -- 5.7 Conclusion -- 6 Data Preprocessing -- 6.1 Introduction -- 6.2 Data Preprocessing in Action -- 6.2.1 Characterizing Data |
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6.2.2 Dimensionality Reduction and Data Transformation -- 6.2.3 Data Enrichment and Validation -- 6.3 Data Preprocessing Tools and Usage -- 6.3.1 Web Usage Mining (WUM) -- 6.3.2 Data Stream Mining (Stream Learning) -- 6.3.3 Knowledge Discovery from Social Media -- 6.4 Conclusion -- Part IV Analytical Methods -- 7 Social Media Analytics -- 7.1 Introduction -- 7.2 Content Analysis -- 7.3 Sentiment and Emotion Analysis -- 7.4 Social Network Analysis -- 7.5 Statistical Analysis -- 7.6 Multimedia Content Analysis -- 7.7 The Benefits of Social Media Analytics Tools |
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7.8 Recommendations for Selecting Social Media Analytics Tool -- 7.9 Tracking Social Media Performance Using Social Media Analytics Tools -- 8 Search Analytics -- 8.1 Review of Search Analytics -- 8.1.1 What is a Search Log? -- 8.2 Process of Search Log Analysis -- 8.2.1 Data Collection -- 8.2.2 Fields in a Standard Search Log -- 8.2.3 Data Preparation -- 8.2.4 Cleaning the Data -- 8.2.5 Normalizing Searching Episodes -- 8.3 Data Analysis -- 8.3.1 Analysis Levels -- 8.3.2 Conducting the Data Analysis -- 8.4 Discussion -- 8.5 Conclusions -- 9 Persona Analytics -- 9.1 What is Persona Analytics? |
| Summary |
This book presents the foundations of using analytics from the laboratory, social media platforms, and the web. The authors cover key topics including analytics strategy, data gathering approaches, data preprocessing, data quality assessment, analytical methods, tools, and validation methods. The book includes chapters explaining web analytics, social media analytics, and how to create an analytics strategy. The authors also cover on data sources, such as online surveys, crowdsourcing, eye tracking, mouse tracking, social media APIs, search logs, and analytics triangulation. The book also discusses analytical tools for social media analytics, search analytics, persona analytics, user studies, and website analytics. The authors conclude by examining the validity of online analytics |
| Notes |
9.2 Why is Persona Analytics Needed? |
| Bibliography |
Includes bibliographical references |
| Notes |
Online resource; title from PDF title page (SpringerLink, viewed September 19, 2023) |
| Subject |
Quantitative research -- Data processing
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Data mining.
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Big data.
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Big data.
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Data mining.
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| Form |
Electronic book
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| Author |
Aldous, Kholoud K
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Salminen, Joni.
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Almerekhi, Hind
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Jung, Soon-gyo.
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| ISBN |
9783031419331 |
|
3031419332 |
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