Social Data Analytics
- Length: 238 pages
- Edition: 1
- Language: English
- Publisher: Routledge
- Publication Date: 2022-08-01
- ISBN-10: 1032196270
- ISBN-13: 9781032196275
- Sales Rank: #0 (See Top 100 Books)
This book is an introduction to social data analytics along with its challenges and opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on concepts, techniques and methods for organizing, curating, processing, analyzing, and visualizing big social data: from text to image and video analytics. It provides novel techniques in storytelling with social data to facilitate the knowledge and fact discovery. The book covers a large body of knowledge that will help practitioners and researchers in understanding the underlying concepts, problems, methods, tools and techniques involved in modern social data analytics. It also provides real-world applications of social data analytics, including: Sales and Marketing, Influence Maximization, Situational Awareness, customer success and Segmentation, and performance analysis of the industry. It provides a deep knowledge in social data analytics by comprehensively classifying the current state of research, by describing in-depth techniques and methods, and by highlighting future research directions. Lecturers will find a wealth of material to choose from for a variety of courses, ranging from undergraduate courses in data science to graduate courses in data analytics.
Cover Title Page Copyright Page Dedication Preface Table of Contents Foreword 1. Social Data Analytics: Challenges and Opportunities 1.1 Understanding Social Data 1.2 Organizing Social Data 1.2.1 Social Data Volume 1.2.2 Social Data Variety 1.2.3 Social Data Velocity 1.2.4 Social Data and Metadata 1.3 Curating Social Data 1.4 Processing Social Data 1.5 Summarizing Social Data 1.6 Storytelling with Social Data 1.7 Social Media Text Analytics 1.8 Social Image and Video Data Analytic 1.9 The Future of Personalization 1.10 Social Data Analytics Applications 1.11 Goals, Structure, and Organization 2. Organizing Social Data 2.1 From Data to Big Data 2.1.1 Big Data 2.1.2 NoSQL: The Need for New Database Management Systems 2.2 Capturing Social Data 2.3 Organizing Social Data 2.4 Warehousing Social Data 2.5 Social Data Provenance 2.5.1 Provenance Representation 2.5.2 Temporal Databases and Graphs 2.6 Data Lakes 2.6.1 Data Lake as a Service 2.6.2 Index and Federated Search 2.6.3 Security and Access Control 2.7 Concluding Remarks and Discussion 3. Curating Social Data 3.1 Social Data Curation: Cleaning, Integration, and Transformation 3.1.1 Identifying Relevant Data Sources 3.1.2 Ingesting Data and Knowledge 3.1.3 Data Cleaning 3.1.4 Data Integration 3.1.5 Data Transformation 3.2 Social Data Curation: Adding Value 3.2.1 Extraction 3.2.2 Correction and Enrichment 3.2.3 Linking 3.2.4 Summarization 3.3 Knowledge Lakes 3.4 Concluding Remarks and Discussion 4. Social Media Text Analytics 4.1 Text Analytics: Overview 4.1.1 Text Preprocessing 4.1.2 Text Representation 4.1.3 Knowledge Discovery 4.2 Social Data Text Analytics: Challenges and Opportunities 4.2.1 Time Sensitivity 4.2.2 Format and Style 4.3 Social Data Text Analytics 4.3.1 Event Detection 4.3.2 Social Data Tagging 4.3.3 Topic Modeling 4.3.4 Social Data Text Classification 4.3.5 Sentiment and Opinion Extraction 4.3.6 Linking Textual Data and Social Metadata 4.4 Concluding Remarks and Discussion 5. Social Media Image and Video Analytics 5.1 Image and Video Analytic: Overview 5.2 Image and Video Analytic: Opportunities and Challenges 5.2.1 Opportunities 5.2.2 Challenges 5.3 Image and Video Detection and Recognition 5.3.1 Object Detection in Images and Video Frames 5.3.2 Face Detection and Recognition 5.4 Storytelling with Image and Video Data 5.4.1 Image and Video Captioning 5.4.2 Location Identification 5.5 3D Posts on Social Media 5.5.1 3D Content Sharing 5.5.2 Light Field Technology 5.6 Concluding Remarks and Discussion 6. Summarizing Social Data 6.1 Automatic Text Summarization: Overview 6.1.1 Text Summarization v. Text Compression 6.2 Social Data Summarization: Challenges and Opportunities 6.3 Social Data Summarization: Generic Approaches 6.3.1 Abstractive Summarization 6.3.2 Extractive Summarization 6.3.3 Hybrid Extractive and Abstractive Summarization 6.3.4 Structured Summarization 6.3.5 Interactive and Personalized Summarization 6.4 Micro-blog Data Summarization 6.4.1 Time-aware Summarization 6.4.2 Event-based Summarization 6.4.3 Opinion-based Summarization 6.5 Evaluation Techniques 6.6 Concluding Remarks and Discussion 7. Storytelling with Social Data 7.1 Storytelling with Social Data: Overview 7.1.1 Challenges and Opportunities 7.2 Data-driven Storytelling via Visualization 7.2.1 Defining Objectives and Knowing the Audience 7.2.2 Identifying a Compelling Narrative 7.2.3 Incorporating Key Elements 7.2.4 Transparency 7.2.5 Visualization Method 7.3 Visualization Techniques 7.3.1 Static Data Visualization 7.3.2 Interactive Data Visualization 7.3.3 Adaptive Data Visualization 7.4 Concluding Remarks and Discussion 8. Social Data and Recommender Systems: The Future of Personalization 8.1 Introduction 8.1.1 Overview of Recommendation Approaches 8.1.2 Collaborative Filtering Approaches 8.1.3 Content-Based Approaches 8.2 Social Recommendation and Personalization 8.2.1 Social Data 8.2.2 Trust-aware Recommendation 8.2.3 Context-aware Recommendation 8.2.4 Temporal Recommendation 8.2.5 Cross-Domain Recommendation 8.2.6 Group Recommendation 8.3 Bias in Social Recommendation 8.4 Application Domains 8.4.1 Video Domain 8.4.2 Music Domain 8.4.3 Fashion Domain 8.4.4 Tourism Domain 8.4.5 Food Domain 8.5 Concluding Remarks and Discussion 9. Social Data Analytics Applications 9.1 Social Data and Trust 9.2 Bias in Social Data 9.3 Personality Detection from Social Data 9.4 Sentiment Analysis of Social Data 9.5 Personalization with Social Data 9.6 Sales and Marketing: Creating Successful Campaigns with Social Media Marketing Analytics 9.7 Influence Maximization: Identify Influencers for Brands and Industries 9.8 Situational Awareness: Discover Trending Topics 9.9 Social Media Information Discovery: From Topic Trends to Sentiment Ratio 9.10 Linking Social Media Performance to Business and Revenue Growth 9.11 Performance Analysis of the Industry 9.12 Concluding Remarks and Discussion References Index
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