Probabilistic Approaches For Social Media Analysis Data Community And Influence
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| Author | : Kun Yue |
| Publisher | : |
| Total Pages | : 290 |
| Release | : 2020 |
| Genre | : Content analysis (Communication) |
| ISBN | : 9811207380 |
"This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle. The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases"--
| Author | : Kun Yue |
| Publisher | : World Scientific |
| Total Pages | : 290 |
| Release | : 2020-02-24 |
| Genre | : Computers |
| ISBN | : 9811207399 |
This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle.The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases.
| Author | : Chengliang Liu |
| Publisher | : World Scientific |
| Total Pages | : 551 |
| Release | : 2023-12-06 |
| Genre | : Business & Economics |
| ISBN | : 9811274975 |
Technology transfer studies are usually framed through Economics and Management Sciences, but this volume Geography of Technology Transfer in China seeks to reveal the mechanism of technology transfer from the geographical perspective. It not only depicts the spatial evolution laws of glocal technology transfer networks, but also uses regression models to uncover the two-way effects between the networks and innovative capacity. In addition, this book highlights the integration and interaction of networks on both the global and local scales. A theoretical framework on glocal networks of technology transfer is established based on a series of economic geography bases in order to depict the spatial differences and coupling mechanism among multi-scaled networks in China.This book consists of 5 parts and 10 chapters, which illustrate the background, theoretical basis, spatial evolution, dual-way influences, and policy implications of technology transfer in China, presenting a clear structure both theoretically and empirically. The book begins with the 'what', 'why', and 'how' questions behind geographical studies on technology transfer to clarify the purpose of the book and its differentiation from present technology transfer studies. Thereafter, it discusses the 'holy trinity' framework of glocal technology transfer networks consisting of cultural, territorial, and networked subsystems. To this end, the spatial evolution of the technology transfer is highlighted through soical network analysis, which aims at depicting the geographical rules of China's technology transfer networks at global, domestic, and regional scales. Based on these discoveries, the next part of the book further analyzes, through a series of regression models such as ERGM and NBRM, the kinds of determinants which have influenced the network size and how the network has in turn affected local innovation capacity . Lastly, the policy implications connect the findings of empirical studies with the operability of the national innovation system. On the whole, this book extensively covers the theoretical, empirical, and practical applications of the geography of technology transfer in China.
| Author | : Bian Wu |
| Publisher | : World Scientific |
| Total Pages | : 214 |
| Release | : 2021-11-24 |
| Genre | : Education |
| ISBN | : 981123292X |
What is data intelligence? How can data intelligence influence education system systematically? The paradigm shift of scientific research implies a coming age of data-driven educational research and practice. This book presents research and practice of data intelligence in education from three levels: (i) educational governance, (ii) teaching practice, and (iii) student learning. Each chapter gives an analysis of fundamental knowledge, key themes, the state-of-the-art technologies and education application cases. This interdisciplinary book is essential reading for anyone interested in applying big data technology in education and for different stakeholders including education administrators, teachers, students, and researchers to broaden their minds to wisely use educational data to solve complex problems in the education field.
| Author | : Xuanxi Li |
| Publisher | : World Scientific |
| Total Pages | : 320 |
| Release | : 2022-01-05 |
| Genre | : Education |
| ISBN | : 9811236933 |
This book provides an example of the capitalization of computer and wiki technology to support collaborative writing among Mainland Chinese upper primary school students. It presents the results of a study showing the application of the Design-Based Research (DBR) methodology to design a Wiki-based Collaborative Process Writing Pedagogy (WCPWP) to help students with their writing in the Chinese context. The WCPWP is designed and developed based on social constructivist theory and the social view of writing process theory, as well as in consideration of the Technological, Pedagogical, and Content Knowledge (TPACK) framework.Primarily aimed at researchers and practitioners in the fields of collaborative learning, TPACK, and Chinese writing, as well as Chinese language educators, this book will also deepen primary educators' understanding of the links among technology, pedagogy and content, and guide educators in the integration of social media, as well as the design of effective matching pedagogic strategies, in their teaching of writing.
| Author | : Junhua Fang |
| Publisher | : World Scientific |
| Total Pages | : 259 |
| Release | : 2020-05-19 |
| Genre | : Computers |
| ISBN | : 9811216169 |
This illustrative compendium analyzes the load balancing problem in distributed stream processing systems and explores a set of high-performance real-time processing scheme based on key-based balancing strategy, join-matrix model and fault tolerance mechanisms.The volume succinctly provides the theoretical support for the proposed techniques. Through a rich set of experiments and comparisons with the other state-of-the-art techniques using both standard benchmarks and real data sets, the book comprehensively verifies the correctness and effectiveness of the proposed methods.This unique title is an excellent reference text for researchers in the fields of distributed stream processing, parallel system, cloud computing, etc.
| Author | : Qiwen Dong |
| Publisher | : World Scientific |
| Total Pages | : 267 |
| Release | : 2020-06-05 |
| Genre | : Computers |
| ISBN | : 9811212961 |
Conceived as a cross between natural language processing methods and biological sequences in DNA, RNA and protein, biological language model is a new scientific research topic in bioinformatics that has been extensively studied by the authors. The basic theory and applications of this model are presented in this book to serve as an reference for graduate students and researchers.
| Author | : Jianpan Wang |
| Publisher | : World Scientific |
| Total Pages | : 593 |
| Release | : 2021-01-28 |
| Genre | : Mathematics |
| ISBN | : 9814713961 |
Our collected work contains mathematics education research papers. Comparative studies of school textbooks cover content selection, compilation style, representation method, design of examples and exercises, mathematics investigation, the use of information technology, and composite difficulty level, to name a few. Other papers included are about representation of basic mathematical thought in school textbooks, a study on the compilation features of elementary school textbooks, and a survey of the effect of using new elementary school textbooks.
| Author | : Gheorghita Bordianu |
| Publisher | : |
| Total Pages | : |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
"Social network analysis is an important cross-disciplinary area of research, with applications in fields such as biology, epidemiology, marketing and even politics. Influence maximization is the problem of finding the set of seed nodes in an information diffusion process that guarantees maximum spread of influence in a social network, given its structure. Most approaches to this problem make two assumptions. First, the global structure of the network is known. Second, influence probabilities between any two nodes are known beforehand, which is rarely the case in practical settings. In this thesis we propose a different approach to the problem of learning those influence probabilities from past data, using only the local structure of the social network. The method is grounded in unsupervised machine learning techniques and is based on a form of hierarchical clustering, allowing us to distinguish between influential and the influenceable nodes. Finally, we provide empirical results using real data extracted from Facebook." --
| Author | : Miltiadis D. Lytras |
| Publisher | : MDPI |
| Total Pages | : 416 |
| Release | : 2020-03-19 |
| Genre | : Technology & Engineering |
| ISBN | : 3039282204 |
A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.
