Social Data Analytics

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 a Full Professor of Data Science and the Director of AI-enabled Processes University. 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 a Master and Bachelor in Computer Science with First Class Honours. Amin has contributed to many research and industry projects, where he was the R&D Team Lead and Key Researcher in the ’Case Walls and Data Curation Foundry’ and ’Big Data for Intelligence’ projects in Australia. Amin has been recognized as a lead researcher in Big-Data/Data/Process Analytics and has served as Keynote Speaker, General-Chair, PC-Chair, Organisation-Chair, and program committee member in top international conferences. He is the leading author of the book entitled Process Analytics, co-authored with other high-profile researchers in UNSW and IBM research, recently published by Springer. Amin secured over ＄10 Million Research Grants for AI-Enabled and Data-Centric projects.

Samira Ghodratnama is a Senior Researcher and Data Scientist at Grainger Technology Group, USA, working on real-world problems related to Natural Language Processing (NLP). She is also a research fellow at Arizona State University (ASU), 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. Her Ph.D. Toward Personalized and Humanin-the-Loop Document Summarization won the innovation award from the Data Analytics Research Lab at Macquarie University. Samira also holds a Masters in Artificial

Intelligence (AI) and a Bachelor in Computer Science with First Class Honours. Her main research interests include machine learning and Natural Language Processing, including personalization, summarization, and information extraction.

Mehdi Elahi is an Associate Professor at the University of Bergen, Norway and an 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 Elahi obtained his Ph.D. degree in Computer Science and has published more than 80 peer-reviewed journal and conference articles. His research has mainly focused on AI, Data Science, and Cognitive Science and their potential industrial applications such as recommendation and personalization systems. He has co-invented and co-owned an AI-related US-patent and received prestigious research credits from big-tech IT industry (i.e., Amazon and Google). He has organized international Data Challenges together with top companies (i.e., Spotify and XING).

Helia Farhood is a 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. Helia also holds a Master in Computer Science and a Bachelor 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. She has many years of experience in industry-led projects and has been involved in the Sydney train project for congestion control and working with CCTV cameras in Australia. Helia’s research interests include Artificial Intelligence (AI), Machine Learning, and Image Processing.