This book includes chapters which discuss effective and efficient approaches in dealing with various aspects of social media analysis by using machine learning techniques from clustering to deep learning. A variety of theoretical aspects, application domains and case studies are covered to highlight how it is affordable to maximize the benefit of various applications from postings on social media platforms. Social media platforms have significantly influenced and reshaped various social aspects. They have set new means of communication and interaction between people, turning the whole world into a small village where people with internet connect can easily communicate without feeling any barriers. This has attracted the attention of researchers who have developed techniques and tools capable of studying various aspects of posts on social media platforms with main concentration on Twitter. This book addresses challenging applications in this dynamic domain where it is not possible to continue applying conventional techniques in studying social media postings. The content of this book helps the reader in developing own perspective about how to benefit from machine learning techniques in dealing with social media postings and how social media postings may directly influence various applications.

Autorentext

Tansel Özyer is a professor of Computer Engineering at Ankara Medipol University, Turkey. He completed his PhD in Computer Science, University of Calgary. He received his MSc and BSc from Computer Engineering departments of METU and Bilkent University. Research interests are data science, machine learning, bioinformatics, XML, mobile databases, and computer vision.