Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach
This study examines the words and situations that trigger and those that do not trigger a hotel response when customers post negative online feedback. The research explores, through sentiment analysis, bigrams, trigrams, and word networking, the valence of online reviews of five important hotels in...
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| Format: | Article |
| Language: | English |
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University of Warsaw
2023-01-01
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| Series: | Journal of Marketing and Consumer Behaviour in Emerging Markets |
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| Online Access: | https://press.wz.uw.edu.pl/jmcbem/vol2023/iss1/3/ |
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| author | DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan |
| author_facet | DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan |
| author_sort | DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan |
| collection | DOAJ |
| description | This study examines the words and situations that trigger and those that do not trigger a hotel response when customers post negative online feedback. The research explores, through sentiment analysis, bigrams, trigrams, and word networking, the valence of online reviews of five important hotels in Las Vegas. Only the feedback that has been categorized as negative by the algorithm is selected. In correspondence to this feedback, the existence of answers from the hotels is checked together with the response style. While the negative valence of the feedback can represent a mixture of subjective and objective emotions, there are common features present in their expression. On the responses side from the hotel, not all the reviews receive attention. As such, the negative feedback words are extracted and separated into those that belong to reviews that obtain a response and those that do not. The replies are standardised by following an established pattern. This paper aims to contribute to a prominent issue in tourism that is little tackled: responses to feedback. The findings may help the hotels’ management explore different paths to improve their services and responses alike. Behavioural marketing researchers might want to use these results to confirm the existence of such patterns in different datasets or situations. |
| format | Article |
| id | doaj-art-7380a15c4f4d44ec924bef093bdcb7a0 |
| institution | Kabale University |
| issn | 2449-6634 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | University of Warsaw |
| record_format | Article |
| series | Journal of Marketing and Consumer Behaviour in Emerging Markets |
| spelling | doaj-art-7380a15c4f4d44ec924bef093bdcb7a02025-02-05T12:07:39ZengUniversity of WarsawJournal of Marketing and Consumer Behaviour in Emerging Markets2449-66342023-01-0120231395010.7172/2449-6634.jmcbem.2023.1.3Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis ApproachDOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan0https://orcid.org/0000-0002-7251-7899Modul University, Vienna, AustriaThis study examines the words and situations that trigger and those that do not trigger a hotel response when customers post negative online feedback. The research explores, through sentiment analysis, bigrams, trigrams, and word networking, the valence of online reviews of five important hotels in Las Vegas. Only the feedback that has been categorized as negative by the algorithm is selected. In correspondence to this feedback, the existence of answers from the hotels is checked together with the response style. While the negative valence of the feedback can represent a mixture of subjective and objective emotions, there are common features present in their expression. On the responses side from the hotel, not all the reviews receive attention. As such, the negative feedback words are extracted and separated into those that belong to reviews that obtain a response and those that do not. The replies are standardised by following an established pattern. This paper aims to contribute to a prominent issue in tourism that is little tackled: responses to feedback. The findings may help the hotels’ management explore different paths to improve their services and responses alike. Behavioural marketing researchers might want to use these results to confirm the existence of such patterns in different datasets or situations.https://press.wz.uw.edu.pl/jmcbem/vol2023/iss1/3/sentiment analysistourismhotelsmarketingcustomer’s opinions |
| spellingShingle | DOI: 10.7172/2449-6634.jmcbem.2023.1.3 Journal of Marketing and Consumer Behaviour in Emerging Markets 1(16)2023 39 (39–50) © 2023 Authors. This is an open access journal distributed under the Creative Commons BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Daniel Dan Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach Journal of Marketing and Consumer Behaviour in Emerging Markets sentiment analysis tourism hotels marketing customer’s opinions |
| title | Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach |
| title_full | Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach |
| title_fullStr | Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach |
| title_full_unstemmed | Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach |
| title_short | Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach |
| title_sort | exploring the impact of negative words used in online feedback in hotel industry a sentiment analysis n gram and text network analysis approach |
| topic | sentiment analysis tourism hotels marketing customer’s opinions |
| url | https://press.wz.uw.edu.pl/jmcbem/vol2023/iss1/3/ |
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