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This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.
Social sciences --- Digital humanities. --- Big data --- Data processing. --- Social aspects. --- Data sets, Large --- Large data sets --- Data sets --- Humanities --- Data processing --- Information technology --- Data mining. --- Behavioral economics. --- Big data. --- Natural language processing (Computer science). --- Philosophy. --- Political science. --- Data Mining and Knowledge Discovery. --- Behavioral/Experimental Economics. --- Big Data/Analytics. --- Natural Language Processing (NLP). --- Philosophy of Technology. --- Political Science. --- Administration --- Civil government --- Commonwealth, The --- Government --- Political theory --- Political thought --- Politics --- Science, Political --- State, The --- Mental philosophy --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Behavioral economics --- Behavioural economics --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching
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This edited volume focuses on big data implications for computational social science and humanities from management to usage. The first part of the book covers geographic data, text corpus data, and social media data, and exemplifies their concrete applications in a wide range of fields including anthropology, economics, finance, geography, history, linguistics, political science, psychology, public health, and mass communications. The second part of the book provides a panoramic view of the development of big data in the fields of computational social sciences and humanities. The following questions are addressed: why is there a need for novel data governance for this new type of data?, why is big data important for social scientists?, and how will it revolutionize the way social scientists conduct research? With the advent of the information age and technologies such as Web 2.0, ubiquitous computing, wearable devices, and the Internet of Things, digital society has fundamentally changed what we now know as "data", the very use of this data, and what we now call "knowledge". Big data has become the standard in social sciences, and has made these sciences more computational. Big Data in Computational Social Science and Humanities will appeal to graduate students and researchers working in the many subfields of the social sciences and humanities.
Philosophy --- Politics --- Engineering sciences. Technology --- Industrial psychology --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- gedrag (mensen) --- NLP (neurolinguïstisch programmeren) --- datamining --- IoT (Internet of Things) --- wearables --- big data --- filosofie --- politiek --- gegevensanalyse --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- data acquisition
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This handbook provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics.
Economics --- Economics, Mathematical. --- Finance --- Data processing.
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Social sciences (general) --- Economics --- Computer. Automation --- economie --- informatica --- sociale wetenschappen --- methodologieën
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Intelligent agents (Computer software) --- Management science --- Data processing
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Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results. Chen, Wang, and Kuo have grouped the 12 contributions following their introductory chapter into applications of fuzzy logic, neural networks (including self-organizing maps and support vector machines), and evolutionary computation. All chapters were selected either by invitation or based on a careful selection and extension of best papers from the International Workshop on Computational Intelligence in Economics and Finance in 2005. Overall, the book offers researchers an excellent overview of current advances and applications of computational intelligence techniques to economics and finance problems.
Economics -- Data processing. --- Economics, Mathematical. --- Economics. --- Finance -- Data processing. --- Mechanical Engineering --- Engineering & Applied Sciences --- Business & Economics --- Economic Theory --- Computer Science --- Mechanical Engineering - General --- Information Technology --- Artificial Intelligence --- Economics --- Finance --- Data processing. --- Mathematical economics --- Mathematics --- Computer science. --- Finance. --- Artificial intelligence. --- Application software. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Finance, general. --- Computer Appl. in Administrative Data Processing. --- Information Systems Applications (incl. Internet). --- Econometrics --- Methodology --- Information systems. --- Artificial Intelligence. --- Funding --- Funds --- Currency question --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Artificial intelligence --- Financial applications. --- Data processing
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The special session on Decision Economics (DECON) is a scientific forum held annually and intended to share ideas, projects, research results, models and experiences associated with the complexity of behavioural decision processes and socio‐economic phenomena. DECON 2017 was held at the Polytechnic of Porto, ISEP, Portugal, as part of the 14th International Conference on Distributed Computing and Artificial Intelligence. For the second consecutive year, the Editors of this book have drawn inspiration from Herbert A. Simon’s immense body of work and argue that Simon precipitated something akin to a revolution in microeconomics focused on the concept of decision‐making. Further, it is worth noting that the recognition of relevant decision‐making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business management, operations, and production. Therefore, decision‐making issues are of fundamental importance in all branches of economics addressed both deductively and inductively. Not surprisingly, the study of decision‐making has seen growing empirical research efforts in the economic literature over the last sixty years and, more recently, a variety of insightful cutting‐edge experimental, behavioural and computational approaches. Additionally, the awareness regarding generalizations and reductions to express economic concepts has led, on the one hand, to an increasing risk of spreading the language of mathematics as a rhetorical tool and, on the other hand, to an oversimplification and overlooking of some crucial details, especially when it comes to human decisions and, hence, economic behaviour. That awareness, however, has helped to produce an extraordinary volume of empirical research aimed at discovering how economic agents cope with complex decisions. In this sense, the international scientific community acknowledges Herbert A. Simon’s research endeavours to understand the processes involved in economic decision‐making and their implications for the advancement of economic professions. Within the field of decision‐making, indeed, Simon’s rejection of the standard decision‐making models used in neoclassical economics inspired social scientists worldwide to develop research programmes in order to study decision‐making empirically. The main achievements concern decision‐making for individuals, firms, markets, governments, institutions, and, last but not least, science and research.
Artificial intelligence --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Economic theory. --- Computational Intelligence. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Artificial Intelligence (incl. Robotics). --- Economic theory --- Political economy --- Social sciences --- Economic man --- Intelligence, Computational --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Artificial Intelligence.
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The special session on Decision Economics (DECON) is a scientific forum held annually, which is focused on sharing ideas, projects, research results, models, and experiences associated with the complexity of behavioural decision processes and socio‐economic phenomena. In 2018, DECON was held at Campus Tecnológico de la Fábrica de Armas, University of Castilla-La Mancha, Toledo, Spain, as part of the 15th International Conference on Distributed Computing and Artificial Intelligence. For the third consecutive year, this book have drawn inspiration from Herbert A. Simon’s interdisciplinary legacy and, in particular, is devoted to designs, models, and techniques for boundedly rational decisions, involving several fields of study and expertise. It is worth noting that the recognition of relevant decision‐making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, small and international business management, operations, and production. Therefore, decision‐making issues are of fundamental importance in all branches of economics addressed with different methodological approaches. As a matter of fact, the study of decision‐making has become the focus of intense research efforts, both theoretical and applied, forming a veritable bridge between theory and practice as well as science and business organisations, whose pillars are based on insightful cutting‐edge experimental, behavioural, and computational approaches on the one hand, and celebrating the value of science as well as the close relationship between economics and complexity on the other. In this respect, the international scientific community acknowledges Herbert A. Simon’s research endeavours to understand the processes involved in economic decision‐making and their implications for the advancement of economic professions. Within the field of decision‐making, indeed, Simon has become a mainstay of bounded rationality and satisficing. His rejection of the standard (unrealistic) decision‐making models adopted by neoclassical economists inspired social scientists worldwide with the purpose to develop research programmes aimed at studying decision‐making empirically, experimentally, and computationally. The main achievements concern decision‐making for individuals, firms, markets, governments, institutions, and, last but not least, science and research. This book of selected papers tackles these issues that Simon broached in a professional career spanning more than sixty years. The Editors of this book dedicated it to Herb.
Decision making. --- Engineering. --- Artificial intelligence. --- Economic theory. --- Computational Intelligence. --- Artificial Intelligence. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Economic theory --- Political economy --- Social sciences --- Economic man --- Computational intelligence. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Econometrics. --- Quantitative Economics. --- Economics, Mathematical --- Statistics
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Agent-based modeling/simulation is an emergent approach to the analysis of social and economic systems. It provides a bottom-up experimental method to be applied to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. This book includes selected papers presented at the Sixth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Taipei in 2009. We have 39 presentations in the conference, and 14 papers are selected to be included in this volume. These 14 papers are then grouped into six parts: Agent-based financial markets; Financial forecasting and investment; Cognitive modeling of agents; Complexity and policy analysis; Agent-based modeling of good societies; and Miscellany. The research presented here shows the state of the art in this rapidly growing field.
Social sciences (general) --- Economics --- Computer. Automation --- economie --- informatica --- sociale wetenschappen --- methodologieën
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This book is based on the International Conference on Decision Economics (DECON 2019). Highlighting the fact that important decision-making takes place in a range of critical subject areas and research fields, including economics, finance, information systems, psychology, small and international business, management, operations, and production, the book focuses on analytics as an emerging synthesis of sophisticated methodology and large data systems used to guide economic decision-making in an increasingly complex business environment. DECON 2019 was organised by the University of Chieti-Pescara (Italy), the National Chengchi University of Taipei (Taiwan), and the University of Salamanca (Spain), and was held at the Escuela politécnica Superior de Ávila, Spain, from 26th to 28th June, 2019. Sponsored by IEEE Systems Man and Cybernetics Society, Spain Section Chapter, and IEEE Spain Section (Technical Co-Sponsor), IBM, Indra, Viewnext, Global Exchange, AEPIA-and-APPIA, with the funding supporting of the Junta de Castilla y León, Spain (ID: SA267P18-Project co-financed with FEDER funds) .
Electronic data processing --- Distributed processing --- Computational intelligence. --- Machine learning. --- Economic theory. --- Computational Intelligence. --- Machine Learning. --- Economic Theory/Quantitative Economics/Mathematical Methods. --- Economic theory --- Political economy --- Social sciences --- Economic man --- Learning, Machine --- Artificial intelligence --- Machine theory --- Intelligence, Computational --- Soft computing
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