Sentiment Analysis: Extracting Decision-Relevant Knowledge from UGC

Sergej Schmunk (), Wolfram Höpken (), Matthias Fuchs () and Maria Lexhagen ()
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Sergej Schmunk: University of Applied Sciences Ravensburg-Weingarten
Wolfram Höpken: University of Applied Sciences Ravensburg-Weingarten
Matthias Fuchs: Mid-Sweden University
Maria Lexhagen: Mid-Sweden University

A chapter in Information and Communication Technologies in Tourism 2014, 2013, pp 253-265 from Springer

Abstract: Abstract Electronically available user generated content (UGC) dramatically increased in recent years and constitutes a highly relevant information source not only for other customers but also for tourism suppliers. Customer needs and their perception of consumed products can be extracted from UGC and represent a valuable input to product enhancement and customer relationship management. A prerequisite to that end is an automatic extraction of decision-relevant knowledge from UGC with a sufficient quality. This paper presents a novel approach for extracting decision-relevant knowledge from UGC and compares different underlying data mining techniques concerning their accuracy in topic and sentiment detection of textual user reviews. The complete extraction process is implemented and evaluated in the context of the Swedish mountain tourism destination Åre.

Keywords: User generated content; Data mining; Opinion mining; Sentiment analysis (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-03973-2_19

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DOI: 10.1007/978-3-319-03973-2_19

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