Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/19383
Title: A data analytics approach to online tourists' reviews evaluation
Authors: Christodoulou, Evripides 
Gregoriades, Andreas 
Papapanayides, Savvas 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Ordinal Logistic Regression;Sentiment Analysis;Topic Analysis;Tourists' Reviews
Issue Date: May-2020
Source: 22nd International Conference on Enterprise Information Systems, 5-7 May 2020
Link: https://www.scitepress.org/Link.aspx?doi=10.5220%2f0009361000990105
Conference: International Conference on Enterprise Information Systems 
Abstract: This paper utilizes online data of tourists' reviews from TripAdvisor to identify patterns with regards to sentiment and topics discussed by tourists that visit Cyprus, along with the investigation of the effect of tourist culture and purchasing power on reviews' polarity, using logistic regression. The analysis uses natural language processing using the LDA technique and Naïve Bayes sentiment analysis. For the data collection, custom-made python scripts were used. Ordinal logistic regression is used to identify differences among the types of tourists visiting Cyprus, in accordance to culture and purchasing power.
URI: https://hdl.handle.net/20.500.14279/19383
ISBN: 978-989-758-423-7
Rights: © by SCITEPRESS CC BY-NC-ND 4.0
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Conference Papers
Affiliation : Cyprus University of Technology 
American University of Bahrain 
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

Files in This Item:
File Description SizeFormat
ICEIS_2020_61.pdfFulltext457.61 kBAdobe PDFView/Open
CORE Recommender
Show full item record

Page view(s) 50

327
Last Week
3
Last month
24
checked on Apr 27, 2024

Download(s) 20

120
checked on Apr 27, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons