Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism

Gabriele Sottocornola; Fabio Stella; Panagiotis Symeonidis; Markus Zanker; Ines Krajger; Rita Faullant; Erich Schwarz

doi:10.1007/978-981-13-6339-9_8

Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism

Gabriele Sottocornola, Fabio Stella, Panagiotis Symeonidis, Markus Zanker, Ines Krajger, Rita Faullant, Erich Schwarz

Department of Business & Management (DBM)

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

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Abstract

This chapter builds on a dataset where online users of a spa platform participated in an online idea contest providing free-text descriptions of their proposals for spa services. A panel of domain experts annotated these idea descriptions with a score for their innovativeness that serves as ground truth for machine learning experiments. Thus, the contribution lies in the application of topic modeling techniques to free-text idea descriptions in order to automatically identify innovative proposals based on advanced text processing and machine learning. Results of this case study indicate that topic modeling can outperform the ZeroR baseline as well as traditional survey scales for lead user identification and therefore constitute a first step towards exploring this technique for innovation research.

Original language	English
Title of host publication	Big Data and Innovation in Tourism, Travel, and Hospitality : Managerial Approaches, Techniques, and Applications
Editors	Marianna Sigala, Roya Rahimi, Mike Thelwall
Place of Publication	Singapore
Publisher	Springer
Publication date	2019
Pages	115-133
Chapter	8
ISBN (Print)	9789811363382
ISBN (Electronic)	9789811363399
DOIs	https://doi.org/10.1007/978-981-13-6339-9_8
Publication status	Published - 2019

Keywords

Online idea contest
Spa tourism
Topic modeling

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10.1007/978-981-13-6339-9_8

Identifying Innovative Idea Proposals with Topic ModelsAccepted manuscript, 490 KBLicence: Other

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Sottocornola, G., Stella, F., Symeonidis, P., Zanker, M., Krajger, I., Faullant, R., & Schwarz, E. (2019). Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism. In M. Sigala, R. Rahimi, & M. Thelwall (Eds.), Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications (pp. 115-133). Springer. https://doi.org/10.1007/978-981-13-6339-9_8

Sottocornola, Gabriele ; Stella, Fabio ; Symeonidis, Panagiotis et al. / Identifying Innovative Idea Proposals with Topic Models : A Case Study from SPA Tourism. Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications. editor / Marianna Sigala ; Roya Rahimi ; Mike Thelwall. Singapore : Springer, 2019. pp. 115-133

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title = "Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism",

abstract = "This chapter builds on a dataset where online users of a spa platform participated in an online idea contest providing free-text descriptions of their proposals for spa services. A panel of domain experts annotated these idea descriptions with a score for their innovativeness that serves as ground truth for machine learning experiments. Thus, the contribution lies in the application of topic modeling techniques to free-text idea descriptions in order to automatically identify innovative proposals based on advanced text processing and machine learning. Results of this case study indicate that topic modeling can outperform the ZeroR baseline as well as traditional survey scales for lead user identification and therefore constitute a first step towards exploring this technique for innovation research.",

keywords = "Online idea contest, Spa tourism, Topic modeling",

author = "Gabriele Sottocornola and Fabio Stella and Panagiotis Symeonidis and Markus Zanker and Ines Krajger and Rita Faullant and Erich Schwarz",

year = "2019",

doi = "10.1007/978-981-13-6339-9_8",

language = "English",

isbn = "9789811363382",

pages = "115--133",

editor = "Marianna Sigala and Roya Rahimi and Mike Thelwall",

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publisher = "Springer",

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Sottocornola, G, Stella, F, Symeonidis, P, Zanker, M, Krajger, I, Faullant, R & Schwarz, E 2019, Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism. in M Sigala, R Rahimi & M Thelwall (eds), Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications. Springer, Singapore, pp. 115-133. https://doi.org/10.1007/978-981-13-6339-9_8

Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism. / Sottocornola, Gabriele; Stella, Fabio; Symeonidis, Panagiotis et al.
Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications. ed. / Marianna Sigala; Roya Rahimi; Mike Thelwall. Singapore: Springer, 2019. p. 115-133.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

TY - CHAP

T1 - Identifying Innovative Idea Proposals with Topic Models

T2 - A Case Study from SPA Tourism

AU - Sottocornola, Gabriele

AU - Stella, Fabio

AU - Symeonidis, Panagiotis

AU - Zanker, Markus

AU - Krajger, Ines

AU - Faullant, Rita

AU - Schwarz, Erich

PY - 2019

Y1 - 2019

N2 - This chapter builds on a dataset where online users of a spa platform participated in an online idea contest providing free-text descriptions of their proposals for spa services. A panel of domain experts annotated these idea descriptions with a score for their innovativeness that serves as ground truth for machine learning experiments. Thus, the contribution lies in the application of topic modeling techniques to free-text idea descriptions in order to automatically identify innovative proposals based on advanced text processing and machine learning. Results of this case study indicate that topic modeling can outperform the ZeroR baseline as well as traditional survey scales for lead user identification and therefore constitute a first step towards exploring this technique for innovation research.

AB - This chapter builds on a dataset where online users of a spa platform participated in an online idea contest providing free-text descriptions of their proposals for spa services. A panel of domain experts annotated these idea descriptions with a score for their innovativeness that serves as ground truth for machine learning experiments. Thus, the contribution lies in the application of topic modeling techniques to free-text idea descriptions in order to automatically identify innovative proposals based on advanced text processing and machine learning. Results of this case study indicate that topic modeling can outperform the ZeroR baseline as well as traditional survey scales for lead user identification and therefore constitute a first step towards exploring this technique for innovation research.

KW - Online idea contest

KW - Spa tourism

KW - Topic modeling

U2 - 10.1007/978-981-13-6339-9_8

DO - 10.1007/978-981-13-6339-9_8

M3 - Book chapter

SN - 9789811363382

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EP - 133

BT - Big Data and Innovation in Tourism, Travel, and Hospitality

A2 - Sigala, Marianna

A2 - Rahimi, Roya

A2 - Thelwall, Mike

PB - Springer

CY - Singapore

ER -

Sottocornola G, Stella F, Symeonidis P, Zanker M, Krajger I, Faullant R et al. Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism. In Sigala M, Rahimi R, Thelwall M, editors, Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications. Singapore: Springer. 2019. p. 115-133 doi: 10.1007/978-981-13-6339-9_8

Identifying Innovative Idea Proposals with Topic Models: A Case Study from SPA Tourism

Abstract

Keywords

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