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Data Versus Democracy: How Big Data Algorithms Shape Opinions and Alter the Course of History, Shaffer Kris


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Цена: 4268.00р.
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Автор: Shaffer Kris
Название:  Data Versus Democracy: How Big Data Algorithms Shape Opinions and Alter the Course of History
ISBN: 9781484245392
Издательство: Springer
Классификация:










ISBN-10: 1484245393
Обложка/Формат: Paperback
Страницы: 120
Вес: 0.20 кг.
Дата издания: 12.07.2019
Язык: English
Издание: 1st ed.
Иллюстрации: 2 illustrations, black and white; xvii, 120 p. 2 illus.
Размер: 155 x 233 x 16
Читательская аудитория: Professional & vocational
Подзаголовок: How big data algorithms shape opinions and alter the course of history
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
Human attention is in the highest demand it has ever been. The drastic increase in available information has compelled individuals to find a way to sift through the media that is literally at their fingertips. Content recommendation systems have emerged as the technological solution to this social and informational problem, but they’ve also created a bigger crisis in confirming our biases by showing us only, and exactly, what it predicts we want to see.
Data versus Democracy investigates and explores how, in the era of social media, human cognition, algorithmic recommendation systems, and human psychology are all working together to reinforce (and exaggerate) human bias. The dangerous confluence of these factors is driving media narratives, influencing opinions, and possibly changing election results.
In this book, algorithmic recommendations, clickbait, familiarity bias, propaganda, and other pivotal concepts are analyzed and then expanded upon via fascinating and timely case studies: the 2016 US presidential election, Ferguson, GamerGate, international political movements, and more events that come to affect every one of us.
What are the implications of how we engage with information in the digital age? Data versus Democracy explores this topic and an abundance of related crucial questions. We live in a culture vastly different from any that has come before. In a society where engagement is currency, we are the product. Understanding the value of our attention, how organizations operate based on this concept, and how engagement can be used against our best interests is essential in responsibly equipping ourselves against the perils of disinformation.
Who This Book Is For
Individuals who are curious about how social media algorithms work and how they can be manipulated to influence culture. Social media managers, data scientists, data administrators, and educators will find this book particularly relevant to their work.

Дополнительное описание: Part I: The Propaganda Problem.- Chapter 1: Pay Attention: How Information Abundance Affects the Way We Consume Media.- Chapter 2: Cog in the System: How the Limits of Our Brains Leave Us Vulnerable to Cognitive Hacking.- Chapter 3: Swimming Upstream: How



Hands-On Data Structures and Algorithms with Python 2 ed

Автор: Agarwal, Dr Basant, Baka, Benjamin
Название: Hands-On Data Structures and Algorithms with Python 2 ed
ISBN: 1788995570 ISBN-13(EAN): 9781788995573
Издательство: Неизвестно
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Цена: 8458.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Data structures help us to organize and align the data in a very efficient way. This book will surely help you to learn important and essential data structures through Python implementation for better understanding of the concepts.

Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course

Автор: Dan Gusfield
Название: Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course
ISBN: 1108421768 ISBN-13(EAN): 9781108421768
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.

Computational Technologies: A First Course

Автор: Nadezhda M. Afanasyeva,Victor S. Borisov,Aleksandr
Название: Computational Technologies: A First Course
ISBN: 3110359928 ISBN-13(EAN): 9783110359923
Издательство: Walter de Gruyter
Цена: 7429.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: In this book wedescribe the basic elements of present computational technologies that use the algorithmic languages C/C++. The emphasis is on GNU compilers and libraries, FOSS for the solution of computational mathematics problems and visualization of the obtained data. At the beginning, a brief introduction to C is given with emphasis on its easy use in scientific and engineering computations.We describe the basic elements of the language, such as variables, data types, executable statements, functions, arrays, pointers, dynamic memory and file management. After that, we present some observations on the C++ programming language.We discuss the issues of program compiling, linking, and debugging. A quick guide to Eclipse is also presented in the book. The main features for editing, compiling, debugging and application assembling are considered.As examples, wesolve the standard problems of computational mathematics: operations with vectors and matrices, linear algebra problems, solution of nonlinear equations, numerical differentiation and integration, interpolation, initial value problems for ODEs and so on. Finally, basic features ofcomputational technologies are illustrated with model problems. All programs are implemented in C/C++ with using the GSL library. Gnuplot is employed to visualize the results of computations.

Algorithms for Data Science

Автор: Steele
Название: Algorithms for Data Science
ISBN: 3319457950 ISBN-13(EAN): 9783319457956
Издательство: Springer
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Цена: 10976.00 р.
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Описание:

This textbook on practical data analytics unites fundamental principles, algorithms, and data. Algorithms are the keystone of data analytics and the focal point of this textbook. Clear and intuitive explanations of the mathematical and statistical foundations make the algorithms transparent. But practical data analytics requires more than just the foundations. Problems and data are enormously variable and only the most elementary of algorithms can be used without modification. Programming fluency and experience with real and challenging data is indispensable and so the reader is immersed in Python and R and real data analysis. By the end of the book, the reader will have gained the ability to adapt algorithms to new problems and carry out innovative analyses.
This book has three parts:
(a) Data Reduction: Begins with the concepts of data reduction, data maps, and information extraction. The second chapter introduces associative statistics, the mathematical foundation of scalable algorithms and distributed computing. Practical aspects of distributed computing is the subject of the Hadoop and MapReduce chapter.
(b) Extracting Information from Data: Linear regression and data visualization are the principal topics of Part II. The authors dedicate a chapter to the critical domain of Healthcare Analytics for an extended example of practical data analytics. The algorithms and analytics will be of much interest to practitioners interested in utilizing the large and unwieldly data sets of the Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System.
(c) Predictive Analytics Two foundational and widely used algorithms, k-nearest neighbors and naive Bayes, are developed in detail. A chapter is dedicated to forecasting. The last chapter focuses on streaming data and uses publicly accessible data streams originating from the Twitter API and the NASDAQ stock market in the tutorials.This book is intended for a one- or two-semester course in data analytics for upper-division undergraduate and graduate students in mathematics, statistics, and computer science. The prerequisites are kept low, and students with one or two courses in probability or statistics, an exposure to vectors and matrices, and a programming course will have no difficulty. The core material of every chapter is accessible to all with these prerequisites. The chapters often expand at the close with innovations of interest to practitioners of data science. Each chapter includes exercises of varying levels of difficulty. The text is eminently suitable for self-study and an exceptional resource for practitioners.
Modern Computer Algebra

Автор: von zur Gathen
Название: Modern Computer Algebra
ISBN: 1107039037 ISBN-13(EAN): 9781107039032
Издательство: Cambridge Academ
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Цена: 17582.00 р.
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Описание: Designed to accompany one- or two-semester courses for advanced undergraduate or graduate students, this textbook is widely regarded as the `bible of computer algebra`. Its comprehensiveness and reliability also makes it an essential reference for professionals. This updated edition includes an overview of recent improvements in areas like primality testing.

Dynamic Fuzzy Machine Learning

Автор: Li, Fanzhang / Zhang, Li / Zhang, Zhao
Название: Dynamic Fuzzy Machine Learning
ISBN: 3110518708 ISBN-13(EAN): 9783110518702
Издательство: Walter de Gruyter
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Цена: 22439.00 р.
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Описание: Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Geometry and Complexity Theory

Автор: Landsberg JM
Название: Geometry and Complexity Theory
ISBN: 1107199239 ISBN-13(EAN): 9781107199231
Издательство: Cambridge Academ
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Цена: 9662.00 р.
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Описание: A comprehensive introduction to algebraic geometry and representation theory written by a leading expert in the field. For graduate students and researchers in computer science and mathematics, the book demonstrates state-of-the-art techniques to solve real world problems, focusing on P vs NP and the complexity of matrix multiplication.

Network Science

Автор: Barab?si
Название: Network Science
ISBN: 1107076269 ISBN-13(EAN): 9781107076266
Издательство: Cambridge Academ
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Цена: 7762.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of disciplines from physics to the social sciences, is the only book needed for an introduction to network science. In modular format, with clear delineation between undergraduate and graduate material, its unique design is supported by extensive online resources.

Handbook of Approximation Algorithms and Metaheuristics

Название: Handbook of Approximation Algorithms and Metaheuristics
ISBN: 1498770150 ISBN-13(EAN): 9781498770156
Издательство: Taylor&Francis
Рейтинг:
Цена: 71966.00 р.
Наличие на складе: Нет в наличии.

Описание: This handbook reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.

Collaborative Recommendations: Algorithms, Practical Challenges and Applications

Автор: Berkovsky Shlomo, Cantador Ivan, Tikk Domonkos
Название: Collaborative Recommendations: Algorithms, Practical Challenges and Applications
ISBN: 9813275340 ISBN-13(EAN): 9789813275348
Издательство: World Scientific Publishing
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Цена: 38808.00 р.
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Описание:

Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e-commerce, multimedia and Web content. Collaborative-based methods have been the focus of recommender systems research for more than two decades.

The unique feature of the compendium is the technical details of collaborative recommenders. The book chapters include algorithm implementations, elaborate on practical issues faced when deploying these algorithms in large-scale systems, describe various optimizations and decisions made, and list parameters of the algorithms.

This must-have title is a useful reference materials for researchers, IT professionals and those keen to incorporate recommendation technologies into their systems and services.

Sequential and Parallel Algorithms and Data Structures

Название: Sequential and Parallel Algorithms and Data Structures
ISBN: 3030252086 ISBN-13(EAN): 9783030252083
Издательство: Springer
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Цена: 5487.00 р.
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Описание: This undergraduate textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.

Formation methods, models, and hardware implementation of pseudorandom number generators :

Автор: Bilan, Stepan,
Название: Formation methods, models, and hardware implementation of pseudorandom number generators :
ISBN: 1522527737 ISBN-13(EAN): 9781522527732
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 28354.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Modern computing systems preserve all information in intricate binary codes. The evolution of systems and technologies that aid in this preservation process must be continually assessed to ensure that they are keeping up with the demands of society. Formation Methods, Models, and Hardware Implementation of Pseudorandom Number Generators: Emerging Research and Opportunities is a crucial scholarly resource that examines the current methodologies used in number generator construction, and how they pertain to the overall advancement of contemporary computer systems. Featuring coverage on relevant topics such as cellular automata theory, inhomogeneous cells, and sequence generators, this publication is ideal for software engineers, computer programmers, academicians, students, and researchers that are interested in staying abreast of innovative trends within the computer engineering field.


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