Using a sentiment analysis for the examination of tourism blogs – a step by step methodological reflection process

Szepannek Gero (), Westphal Laila (), Gronau Werner () and Lehmann Tine ()
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Szepannek Gero: Professor of Statistics, Business Mathematics and Machine Learning at Stralsund University of Applied Sciences, Germany. Hochschule Stralsund Zur Schwedenschanze 15, 18435 Stralsund Stralsund Germany
Westphal Laila: Software Developer at MPS – Medizinische Planungssysteme GmbH in Freiburg, Germany. Fachbereich 4: Informatik, Kommunikation und Wirtschaft, Hochschule für Technik und Wirtschaft Berlin, Wilhelminenhofstraße 75A, 12459 Berlin Germany
Gronau Werner: Professur für “Tourism, Travel and Transport”, Fakultät Wirtschaft Hochschule Stralsund Zur Schwedenschanze 15, 18435 Stralsund Germany
Lehmann Tine: Professor of International Business at University of Applied Sciences (HTW) Berlin Hochschule für Technik und Wirtschaft Berlin Treskowallee 8, 10318 Berlin Germany

Zeitschrift für Tourismuswissenschaft, 2021, vol. 13, issue 2, 167-190

Abstract: The article at hand is driven by a methodological interest in the opportunities and challenges of applying an automated text mining approach, particularly a sentiment analysis on various tourism blogs at the same time. The study aims to answer the question to what extent advanced computational methods can improve the data acquisition and analysis of unstructured data sets stemming from various blogs and forums. Furthermore, the authors intend to explore to what extent the sentiment analysis is able to objectify the qualitative results identified by an earlier analysis by the authors using content analysis done by thematic coding. For the purpose of the specific tourism research question in this paper a new approach is proposed, which consists of a combination of sentiment analyses, supervised learning, and dimensionality reduction in order to identify terms that strongly load on specific emotions. The contribution indicates on the one hand, that advanced computational methods have their own specific constraints, but on the other hand, are able to provide a richer and deeper analysis following a quantitative approach. Several issues have to be taken into account, such as data protection constraints, the need for data cleaning, such as word stemming, dimension reduction, such as removal of custom stop words, and the development of descent ontologies. On the other hand, the quantitative method also provides, due to its standardised procedure, a less subjective insight in the given content, but is not less time consuming than traditional content analysis.

Keywords: tourism; sentiment analysis; text mining; lasso regression; web scraping (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:touwis:v:13:y:2021:i:2:p:167-190:n:2

DOI: 10.1515/tw-2021-0011

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