Applied data science in tourism : interdisciplinary approaches, methodologies, and applications / Roman Egger, editor.
Egger, Roman, editor.
2022
G155.7 .A56 2022
Available Online

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Title Applied data science in tourism : interdisciplinary approaches, methodologies, and applications / Roman Egger, editor.
ISBN 9783030883898 (electronic bk.)
3030883892 (electronic bk.)
9783030883881
3030883884
DOI https://doi.org/10.1007/978-3-030-88389-8
Published Cham : Springer, [2022]
Copyright ©2022
Language English
Description 1 online resource.
Item Number 10.1007/978-3-030-88389-8 doi
Call Number G155.7 .A56 2022
Dewey Decimal Classification 338.4/7910721
Summary Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science not only in tourism and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them. - Hannes Werthner, Vienna University of Technology. Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism. - Francesco Ricci, Free University of Bozen-Bolzano. This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 16, 2022).
Added Author Egger, Roman, editor.
Series Tourism on the verge.
Available in Other Form Print version: 9783030883881
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Part I: Theoretical Fundaments
AI and Big Data in Tourism
Epistemological Challenges
Data Science and Interdisciplinarity
Data Science and Ethical Issues
Web Scraping
Part II: Machine Learning
Machine Learning in Tourism: A Brief Overview
Feature Engineering
Clustering
Dimensionality Reduction
Classification
Regression
Hyperparameter Tuning
Model Evaluation
Interpretability of Machine Learning Models
Part III: Natural Language Processing
Natural Language Processing (NLP): An Introduction
Text Representations and Word Embeddings
Sentiment Analysis
Topic Modelling
Entity Matching: Matching Entities Between Multiple Data Sources
Knowledge Graphs
Part IV: Additional Methods
Network Analysis
Time Series Analysis
Agent-Based Modelling
Geographic Information System (GIS)
Visual Data Analysis
Software and Tools.

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