Negative Airbnb reviews: an aspect based sentiment analysis approach

Vassilikopoulou, Aikaterini, Kamenidou, Irene and Priporas, Constantinos-Vasilios ORCID logoORCID: (2022) Negative Airbnb reviews: an aspect based sentiment analysis approach. EuroMed Journal of Business . ISSN 1450-2194 [Article] (Published online first) (doi:10.1108/emjb-03-2022-0052)

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Purpose (limit 100 words) The current paper aims at exploring negative aspects in reviews about Airbnb listings in Athens, Greece. Design/methodology/approach (limit 100 words) The aspect-based sentiment approach (ABSA), a subset of sentiment analysis, is used. The study analyzed 8,200 reviews, which had at least one negative aspect. Based on dependency parsing, noun phrases were extracted, and the underlying grammar relationships were used to identify aspect and sentiment terms.
Findings (limit 100 words) The extracted aspect terms were classified into three broad categories, i.e., the location, the amenities and the host. To each of them the associated sentiment was assigned. Based on the results, Airbnb properties could focus on certain aspects related to negative sentiments in order to minimize negative reviews and increase customer satisfaction.
Originality/value (limit 100 words) The study employs the ABSA, which offers more advantages in order to identify multiple conflicting sentiments in Airbnb comments, which is the limitation of the traditional sentiment analysis method.

Item Type: Article
Keywords (uncontrolled): Empirical Research Paper, Airbnb, Negative reviews, Aspect-based sentiment analysis, consumer behavior
Research Areas: A. > Business School > Marketing, Branding and Tourism
Item ID: 35234
Notes on copyright: This author accepted manuscript is deposited under a Creative Commons Attribution 4.0 International (CC BY) licence.
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Depositing User: Jisc Publications Router
Date Deposited: 13 Jun 2022 16:45
Last Modified: 17 Feb 2023 15:06

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