Analysing User Reviews in Tourism with Topic Models
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Clustering techniques such as k-means and statistical models based on probability distribution of reviews in sentiment space were employed in the literature for sentiment analysis of short text data.
“Clustering techniques, such as k-means (Xiang et al., 2015b), and statistical models based on the probability distribution of reviews in sentiment space (Rossetti et al., 2015) were employed in the literature for sentiment analysis of short text data.”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Rossetti et al., 2015
K-mean clustering techniques and statistical models based on probability distribution of reviews in sentiment space were employed on tourism data.
“K-mean clustering techniques and statistical models based on probability distribution of reviews in sentiment space (Rossetti et al., 2015, Xiang et al., 2015b) were also employed on tourism data.”
From Sentiment Analysis in Tourism: Capitalizing on Big Data (2019) · cites this paper as Rossetti et al., 2015
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- Authors
- Rossetti, M., Stella, F., Cao, L., & Zanker, M.
- Affiliations
- University of Milano-Bicocca (IT)
- University of Technology Sydney (AU)
- University of Klagenfurt (AT)
- Corresponding author
- Rossetti, Marco
- Venue
- Information and Communication Technologies in Tourism 2015
- Publisher
- Springer International Publishing
- Published
- 2014-12-27
- Pages
- 47-58
- OpenAlex
- W4238089794
- Cited by
- 13
- References
- 24
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 3 · 2021: 2 · 2017: 2 · 2016: 4
- FWCI
- 4.26
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion)
- Funders
- Australian Government
- European Commission
- European Regional Development Fund
- Interreg
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Keywords
- online reviews, topic modeling, tourism, digital tourism, user-generated content, decision support, recommender systems, Yelp, TripAdvisor, text analysis
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