Xinyue Ye - Böcker

The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques.FeaturesThe first textbook on cloud-based social data analytics with the assistance of Generative AI.Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB.Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization.Analyzes Census and social media data with the latest large language models (LLMs).Provides hands-on exercises with real-world datasets on timely issues.This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.

This comprehensive handbook covers human mobility within urban contexts, integrating academic theories with pragmatic insights and offering a detailed analysis of the diverse facets of human mobility and its substantial impact on the urban landscape, economy, and societal structures. It explains key fundamental concepts, methods, and models, presenting an in-depth exploration of predictive analytics, clustering patterns, advanced trajectory embedding techniques, artificial intelligence, machine learning, geographic information systems (GIS), Internet of Things (IoT), and smart city innovations. The authors include many case studies and examples of urban mobility in practice, making the content relatable and practical for educators, students, researchers, and practitioners.FeaturesProvides a multidisciplinary and holistic understanding of urban mobility with systematic introductions and discussions of theory, methods, technologies, tools, and applicationsCovers a wide range of real-world case studies of urban mobility in practice globally that include data, programming code, and toolsDiscusses cutting-edge technologies involved in mobility data analyticsAddresses practical challenges in data collection and the ethical implications of mobility research, which are crucial for professionals in the fieldOffers future directions of human mobility research under the big data and artificial intelligence (AI) revolutionUrban Human Mobility: Practices, Analytics, and Strategies for Smart Cities is for professionals, academics, and upper-level undergraduate and graduate students in the fields of urban planning/design, GIScience, data mining, and social sciences.

This book reports on the latest, cutting-edge scholarship on integrating social network and spatial analyses in the built environment.  It sheds light on conceptualization and Implementation of such integration, integration for intra-city level analysis, as well as integration for inter-city level analysis. It explores the use of new data sources concerning human and urban dynamics and provides a discussion of how social network and spatial analyses could be synthesized for a more nuanced understanding of the built environment.  As such this book will be a valuable resource for scholars focusing on city-related networks in a number of ‘urban’ disciplines, including but not limited to urban geography, urban informatics,  urban planning, urban sociology, and urban studies.

This book describes how powerful computing technology, emerging big and open data sources, and theoretical perspectives on spatial synthesis have revolutionized the way in which we investigate social sciences and humanities.

This book describes how powerful computing technology, emerging big and open data sources, and theoretical perspectives on spatial synthesis have revolutionized the way in which we investigate social sciences and humanities.