Data Science for Economics and Finance
Data Science for Economics and Finance

Author: Sergio Consoli

Publisher: Springer Nature

Published: 2021

Total Pages: 357

ISBN-13: 3030668916

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This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Sentiment Analysis
Sentiment Analysis

Author: Bing Liu

Publisher: Cambridge University Press

Published: 2020-10-15

Total Pages: 451

ISBN-13: 1108787282

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Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.

Handbook of Natural Language Processing
Handbook of Natural Language Processing

Author: Nitin Indurkhya

Publisher: CRC Press

Published: 2010-02-22

Total Pages: 704

ISBN-13: 142008593X

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The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater

Opinion Mining and Sentiment Analysis
Opinion Mining and Sentiment Analysis

Author: Bo Pang

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 149

ISBN-13: 1601981503

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This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.

CeDEM14
CeDEM14

Author: Parycek, Peter

Publisher: MV-Verlag

Published: 2014

Total Pages: 620

ISBN-13: 3902505354

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Sentiment Analysis in Social Networks
Sentiment Analysis in Social Networks

Author: Federico Alberto Pozzi

Publisher: Morgan Kaufmann

Published: 2016-10-06

Total Pages: 286

ISBN-13: 0128044381

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The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics

Diverse Methods in Customer Relationship Marketing and Management
Diverse Methods in Customer Relationship Marketing and Management

Author: Lee, In

Publisher: IGI Global

Published: 2018-05-25

Total Pages: 350

ISBN-13: 1522556206

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Consumer interaction and engagement are vital components to help marketers maintain a lasting relationship with their customers. By developing positive relationships with consumers, businesses can better maintain their customers’ loyalty. Diverse Methods in Customer Relationship Marketing and Management is a critical scholarly resource that examines how marketing has shifted to a relationship-oriented model. Due to this, there is an increased need for customer relationship marketing and management to emerge as an invaluable approach to strengthening companies and the customer experience. Featuring coverage on a wide range of topics such as relational marketing technology acceptance model, and consumer buying behavior, this book is a vital resource for marketing professionals, managers, retailers, advertising executives, academicians, and researchers seeking current research on the challenges and opportunities in customer relationship marketing and management.

Engineering Applications of Neural Networks
Engineering Applications of Neural Networks

Author: Chrisina Jayne

Publisher: Springer

Published: 2016-08-18

Total Pages: 365

ISBN-13: 3319441884

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This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016. The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.

Affective Computing and Sentiment Analysis
Affective Computing and Sentiment Analysis

Author: Khurshid Ahmad

Publisher: Springer Science & Business Media

Published: 2011-08-24

Total Pages: 158

ISBN-13: 9400717571

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This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated. This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology.

Sentiment Analysis and Opinion Mining
Sentiment Analysis and Opinion Mining

Author: Bing Liu

Publisher: Morgan & Claypool Publishers

Published: 2012

Total Pages: 185

ISBN-13: 1608458849

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Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography