Social Data Analytics
CRC Press (Verlag)
978-1-032-19631-2 (ISBN)
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.
Amin Beheshti is Full Professor of Data Science and the Director of AI-enabled Processes Research Centre at Macquarie University, Sydney, Australia. Amin is also the head of the Data Analytics Research Lab and Adjunct Academic in Computer Science at UNSW Sydney. Amin completed his Ph.D. and Postdoc in Computer Science and Engineering at UNSW Sydney and holds both a master's and bachelor's degree in Computer Science, both with First Class Honours. Amin has been recognized as a high-quality researcher in Big-Data/Data/Process Analytics and served as Keynote Speaker, General-Chair, PC-Chair, Organisation-Chair, and program committee member of top international conferences. Amin has contributed to many research and industry projects, and currently leading over 20 large research projects with highprofile companies. He is the leading author of several books in data, social, and process analytics, co-authored with other high-profile researchers. Samira Ghodratnama is Senior Applied Machine Learning Scientist at Grainger Technology Group, USA, working on real-world problems related to Natural Language Processing (NLP). She is also a research fellow at Macquarie University, Sydney, Australia and Arizona State University, USA, working on complex research problems in the area of text mining, machine learning, and information extraction. Samira has extensive experience building data-centric applications. She holds a Ph.D. in Computer Science from Macquarie University, Sydney, Australia. Mehdi Elahi is Associate Professor at the University of Bergen, Norway and Adjunct Professor at the Norwegian School of Economics, one of the leading business schools in Europe. He also holds an Honorary Associate Professor position at Macquarie University, Sydney, Australia. He is a co-author and WP-Leader of a large-scale SFI project (budget: 26 Million Euro), where he collaborates with the largest international industry players in the Media sector in Norway. Mehdi obtained his Ph.D. degree in Computer Science. His research has mainly focused on AI, Data Science, and Cognitive Science and their potential industrial applications such as recommendation and personalization systems. Helia Farhood is Research Fellow in Data Science at Macquarie University, Sydney, Australia. Helia holds a Ph.D. in Computer Systems and Artificial Intelligence (AI) from the University of Technology Sydney (UTS), Sydney, Australia. She also holds a master's degree in Artificial Intelligence and a bachelor's degree in Computer Engineering with First Class Honours. Helia has extensive experience in Image and Video Processing, and her Ph.D. research focused on 3D reconstruction using light field technology. Helia’s research interests include AI, Machine Learning, and Image Processing.
1. Social Data Analytics: Challenges and Opportunities 2. Organizing Social Data 3. Curating Social Data 4. Social Media Text Analytics 5. Social Media Image and Video Analytics 6. Summarizing Social Data 7. Storytelling with Social Data 8. Social Data and Recommender Systems: The Future of Personalization 9. Social Data Analytics Applications
| Erscheinungsdatum | 13.09.2024 |
|---|---|
| Zusatzinfo | 4 Tables, black and white; 3 Line drawings, color; 3 Line drawings, black and white; 5 Halftones, color; 5 Halftones, black and white; 8 Illustrations, color; 8 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 462 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Sozialwissenschaften ► Kommunikation / Medien ► Journalistik | |
| Wirtschaft ► Volkswirtschaftslehre | |
| ISBN-10 | 1-032-19631-9 / 1032196319 |
| ISBN-13 | 978-1-032-19631-2 / 9781032196312 |
| Zustand | Neuware |
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