Applied Data Science in Tourism
Interdisciplinary Approaches, Methodologies, and Applications
Bibliographic Data
| ID | 19945294 |
|---|---|
| Editors | Roman Egger (0000-0003-4888-6026) |
| Year | 2022 |
| Publication date | 2022-01-01 |
| Open Access | Yes |
| Type | BOOK |
| Venue | Applied Data Science in Tourism (SOURCE_BOOK) |
| Publisher | Springer International Publishing (PUBLISHER • SG) |
| DOI | 10.1007/978-3-030-88389-8 |
| Wikidata | Q126371955 |
| OpenAlex | W4210650276 |
| Open Library | OL34807452M |
| ISBN | 9783030883898 |
| Language | EN |
| Citations received | 7 |
| References cited | 2 |
Archaeology · Data science · Geography · Social media · Social network analysis · Tourism · World Wide Web · Computer Science · Digital Marketing and Social Media
Gastronomic image in the foodstagrammer’s eyes – A machine learning approach
Delineating and Typologizing Urban Innovation Districts Beyond Administrative Boundaries Using Multi-Source Geospatial Data
Can tourism be a mean for promoting inclusive development? A textual analysis of funded projects in Greece
AI-Driven Cultural Storytelling and Tourists’ Behavioral Intentions
A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and Bertopic to Demystify Twitter Posts
Looking behind the scenes at dark tourism
Exploring the Tourism Sustainability Knowledge Network Through Bibliometric Analysis and a Computational Literature Review
| Unique citing works | 7 |
|---|---|
| Citations per year | 1,75 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 6 |