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Authors: Evripides Christodoulou 1 ; Andreas Gregoriades 1 and Savvas Papapanayides 2

Affiliations: 1 Cyprus University of Technology, Limassol, Cyprus ; 2 American University of Bahrain, Bahrain

Keyword(s): Sentiment Analysis, Ordinal Logistic Regression, Topic Analysis, Tourists’ Reviews.

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Christodoulou, E.; Gregoriades, A. and Papapanayides, S. (2020). A Data Analytics Approach to Online Tourists’ Reviews Evaluation. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-423-7; ISSN 2184-4992, SciTePress, pages 99-105. DOI: 10.5220/0009361000990105

@conference{iceis20,
author={Evripides Christodoulou. and Andreas Gregoriades. and Savvas Papapanayides.},
title={A Data Analytics Approach to Online Tourists’ Reviews Evaluation},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2020},
pages={99-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009361000990105},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - A Data Analytics Approach to Online Tourists’ Reviews Evaluation
SN - 978-989-758-423-7
IS - 2184-4992
AU - Christodoulou, E.
AU - Gregoriades, A.
AU - Papapanayides, S.
PY - 2020
SP - 99
EP - 105
DO - 10.5220/0009361000990105
PB - SciTePress

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