The bravo: A framework of building reputation analytics from voice online

Bogeun Jo; Kyung Bae Park; Sung Ho Ha

doi:10.1007/978-3-030-22999-3_66

The bravo: A framework of building reputation analytics from voice online

Bogeun Jo, Kyung Bae Park, Sung Ho Ha

School of Business Administration

Kyungpook National University

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

1 Scopus citations

Abstract

This paper provides a framework to efficiently discover production performance and its application plan by analyzing massive amounts of comments from online review data, especially in the field of hospitality. In order to achieve the goal, two stages of text analytics of sentiment analysis and structural topic model estimating are integrated to classify sentimental polarity of each reviews and elicit hidden dimensions of products or services. Based on these dimensions and polarities, this paper verifies key attributes which impact customer satisfaction by adapting logistic regression. This study extends prior research limitation which focused on discovering the product defect by (1) strength detection, (2) time series analysis, and (3) explanation of the relationship between crucial factors and polarity of the review as a proxy of customer satisfaction. By integrating text analytics from computational linguistic and a traditional statistical method, this paper is expected to contribute on both academical and practical implications.

Original language	English
Title of host publication	Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings
Editors	Franz Wotawa, Ingo Pill, Roxane Koitz-Hristov, Gerhard Friedrich, Moonis Ali
Publisher	Springer Verlag
Pages	777-790
Number of pages	14
ISBN (Print)	9783030229986
DOIs	https://doi.org/10.1007/978-3-030-22999-3_66
State	Published - 2019
Event	32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019 - Graz, Austria Duration: 9 Jul 2019 → 11 Jul 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11606 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019
Country/Territory	Austria
City	Graz
Period	9/07/19 → 11/07/19

Keywords

Customer satisfaction
Sentiment analysis
STM
Text mining

Access to Document

10.1007/978-3-030-22999-3_66

Cite this

Jo, B., Park, K. B., & Ha, S. H. (2019). The bravo: A framework of building reputation analytics from voice online. In F. Wotawa, I. Pill, R. Koitz-Hristov, G. Friedrich, & M. Ali (Eds.), Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings (pp. 777-790). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11606 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-22999-3_66

Jo, Bogeun ; Park, Kyung Bae ; Ha, Sung Ho. / The bravo : A framework of building reputation analytics from voice online. Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings. editor / Franz Wotawa ; Ingo Pill ; Roxane Koitz-Hristov ; Gerhard Friedrich ; Moonis Ali. Springer Verlag, 2019. pp. 777-790 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "This paper provides a framework to efficiently discover production performance and its application plan by analyzing massive amounts of comments from online review data, especially in the field of hospitality. In order to achieve the goal, two stages of text analytics of sentiment analysis and structural topic model estimating are integrated to classify sentimental polarity of each reviews and elicit hidden dimensions of products or services. Based on these dimensions and polarities, this paper verifies key attributes which impact customer satisfaction by adapting logistic regression. This study extends prior research limitation which focused on discovering the product defect by (1) strength detection, (2) time series analysis, and (3) explanation of the relationship between crucial factors and polarity of the review as a proxy of customer satisfaction. By integrating text analytics from computational linguistic and a traditional statistical method, this paper is expected to contribute on both academical and practical implications.",

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Jo, B, Park, KB & Ha, SH 2019, The bravo: A framework of building reputation analytics from voice online. in F Wotawa, I Pill, R Koitz-Hristov, G Friedrich & M Ali (eds), Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11606 LNAI, Springer Verlag, pp. 777-790, 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Graz, Austria, 9/07/19. https://doi.org/10.1007/978-3-030-22999-3_66

The bravo: A framework of building reputation analytics from voice online. / Jo, Bogeun; Park, Kyung Bae; Ha, Sung Ho.
Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings. ed. / Franz Wotawa; Ingo Pill; Roxane Koitz-Hristov; Gerhard Friedrich; Moonis Ali. Springer Verlag, 2019. p. 777-790 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11606 LNAI).

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

TY - GEN

T1 - The bravo

T2 - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019

AU - Jo, Bogeun

AU - Park, Kyung Bae

AU - Ha, Sung Ho

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - This paper provides a framework to efficiently discover production performance and its application plan by analyzing massive amounts of comments from online review data, especially in the field of hospitality. In order to achieve the goal, two stages of text analytics of sentiment analysis and structural topic model estimating are integrated to classify sentimental polarity of each reviews and elicit hidden dimensions of products or services. Based on these dimensions and polarities, this paper verifies key attributes which impact customer satisfaction by adapting logistic regression. This study extends prior research limitation which focused on discovering the product defect by (1) strength detection, (2) time series analysis, and (3) explanation of the relationship between crucial factors and polarity of the review as a proxy of customer satisfaction. By integrating text analytics from computational linguistic and a traditional statistical method, this paper is expected to contribute on both academical and practical implications.

AB - This paper provides a framework to efficiently discover production performance and its application plan by analyzing massive amounts of comments from online review data, especially in the field of hospitality. In order to achieve the goal, two stages of text analytics of sentiment analysis and structural topic model estimating are integrated to classify sentimental polarity of each reviews and elicit hidden dimensions of products or services. Based on these dimensions and polarities, this paper verifies key attributes which impact customer satisfaction by adapting logistic regression. This study extends prior research limitation which focused on discovering the product defect by (1) strength detection, (2) time series analysis, and (3) explanation of the relationship between crucial factors and polarity of the review as a proxy of customer satisfaction. By integrating text analytics from computational linguistic and a traditional statistical method, this paper is expected to contribute on both academical and practical implications.

KW - Customer satisfaction

KW - Sentiment analysis

KW - STM

KW - Text mining

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DO - 10.1007/978-3-030-22999-3_66

M3 - Conference contribution

AN - SCOPUS:85068594944

SN - 9783030229986

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 777

EP - 790

BT - Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings

A2 - Wotawa, Franz

A2 - Pill, Ingo

A2 - Koitz-Hristov, Roxane

A2 - Friedrich, Gerhard

A2 - Ali, Moonis

PB - Springer Verlag

Y2 - 9 July 2019 through 11 July 2019

ER -

Jo B, Park KB, Ha SH. The bravo: A framework of building reputation analytics from voice online. In Wotawa F, Pill I, Koitz-Hristov R, Friedrich G, Ali M, editors, Advances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings. Springer Verlag. 2019. p. 777-790. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-22999-3_66

The bravo: A framework of building reputation analytics from voice online

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