Laeeq Khan

The Data Analytics Advantage (eBook, PDF)

Strategies and Insights to Understand Social Media Content and Audiences

• Format: PDF

Produktbeschreibung

The Data Analytics Advantage is a comprehensive guide that equips readers with the essential skills to analyze and leverage social media data for strategic decision-making. Combining academic principles with case studies, social media analytics expert Laeeq Khan provides a foundational understanding of the field and its importance, introduces cutting-edge trends and tools through interactive tutorials and exercises, and offers a glimpse into future developments, including the potential impact of artificial intelligence. With its balance of technical rigor and accessibility, the textbook requires minimal coding experience while covering a wide range of topics. Using a three-stage framework--discovery, analysis, visualization--Khan emphasizes the importance of question formulation, data collection, and the skillful application of analytical tools; unveils key aspects of social media analytics, from hashtag and temporal analysis to social network analysis, data visualization, and storytelling; introduces readers to various methodologies, including monitoring metrics and KPIs, adopting advanced data visualization techniques, and mastering sentiment and network analysis; and addresses potential challenges in social media analytics, such as data access, privacy, and ethics. Readers will come away with a solid grasp of theoretical concepts as well as hands-on experience through practical exercises, making The Data Analytics Advantage an indispensable resource for students, social media administrators, marketers, and data analysts alike in the rapidly evolving field of social media analytics.

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Produktdetails

• Verlag: OUP eBook
• Seitenzahl: 296
• Erscheinungstermin: 7. August 2025
• Englisch
• ISBN-13: 9780197814253
• Artikelnr.: 75202742

Autorenporträt

Laeeq Khan is Associate Professor and founding Director of the SMART Lab at Ohio University. He specializes in social media, data analytics, AI, and digital engagement. With a Ph.D. from Michigan State University, he is a computational social scientist focused on technology-driven insights. Dr. Khan has published widely on social media engagement, health communication, and misinformation. With a decade of industry consulting and teaching experience, he is committed to mentoring future scholars in media, communication, and business.

Inhaltsangabe

Preface
Chapter 1: Introduction: Analytics Overview
Chapter 2: Social Media Analytics Framework
Chapter 3: Goals, Metrics and Measurement
Chapter 4: Data Gathering, Organizing, and Cleaning
Chapter 5: Textual Data Structuring
Chapter 6: Text Analytics Interpretative Methods and Tools
Chapter 7: Social Network Analysis
Chapter 8: Image and Video Analytics
Chapter 9: Data Visualization
Chapter 10: Spatial Analytics for Social Media
Chapter 11: Integrating Design Thinking into Dashboards and Reports
Chapter 12: Artificial Intelligence and the Future of Social Media Analytics