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Erschienen in:
An Information Systems Design Theory for Digital Broker Platforms Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

Supporting Product Development by a Trend Analysis Tool Applying Aspect-Based Sentiment Detection

verfasst von : Janik Wörner, Daniel Konadl, Isabel Schmid, Susanne Leist

Erschienen in: The Transdisciplinary Reach of Design Science Research

Verlag: Springer International Publishing

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Abstract

Incorporating product trends into innovation processes is imperative for companies to meet customers’ expectations and to stay competitive in fiercely opposing markets. Currently, aspect-based sentiment analysis has proven an effective approach for investigating and tracking towards products and corresponding features from social media. However, existing trend analysis tools on the market that offer aspect-based sentiment analysis capabilities, do not meet the requirements regarding the use case Product Development. Therefore, based on these requirements, we implemented an artifact by following the design science research. We applied our tool to real-world social media data (37,638 Yelp reviews) from one major fast-food restaurant in the US, and thereby demonstrated that our tool is capable of identifying remarkable and fine-grained product trends.

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Vorheriges Kapitel Toward an Information Systems Ontology
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Metadaten
Titel
Supporting Product Development by a Trend Analysis Tool Applying Aspect-Based Sentiment Detection
verfasst von
Janik Wörner
Daniel Konadl
Isabel Schmid
Susanne Leist
Copyright-Jahr
2022
Buch
The Transdisciplinary Reach of Design Science Research

Print ISBN: 978-3-031-06515-6

Electronic ISBN: 978-3-031-06516-3

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-3-031-06516-3_6

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