Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach

Di (Richard) Shang; Zhaoxia Wang; Zhenda Hu

doi:10.1007/978-3-030-78609-0_47

Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach

Di (Richard) Shang, Zhaoxia Wang, Zhenda Hu

Management

Producción científica: Literary contribution

Resumen

There is a rich collection of studies exploring different aspects of consumer brand relationship. Traditional approaches of questionnaires and analysis are based on measurements collected from a relatively small number of survey participants. With the advancements in natural language processing (NLP) techniques, opportunities exist for applying NLP techniques to discover consumer brand relationship from social media platforms that possess a large amount of data on consumer opinion and sentiment. In this study, we review consumer brand relationship analysis focusing on leveraging NLP and machine learning techniques to address some challenges associated with discovering customer brand relationship from social media data and propose a methodological framework for the approach. This study has implications for both academic research and practitioners as it presents an alternative way to investigate consumer brand relationship.

Idioma original	American English
Título de la publicación alojada	Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings
Subtítulo de la publicación alojada	7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I
Editores	Xingming Sun, Xiaorui Zhang, Zhihua Xia, Elisa Bertino
Lugar de publicación	Switzerland
Páginas	533-565
Número de páginas	13
ISBN (versión digital)	978-3-030-78609-0
DOI	https://doi.org/10.1007/978-3-030-78609-0_47
Estado	Published - 2021
Evento	7th International Conference on Artificial Intelligence and Security, ICAIS 2021 - Dublin, Ireland Duración: jul 19 2021 → jul 23 2021

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	12736 LNCS
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conference

Conference	7th International Conference on Artificial Intelligence and Security, ICAIS 2021
País/Territorio	Ireland
Ciudad	Dublin
Período	7/19/21 → 7/23/21

ASJC Scopus Subject Areas

Theoretical Computer Science
General Computer Science

Acceder al documento

10.1007/978-3-030-78609-0_47

https://link.springer.com/chapter/10.1007/978-3-030-78609-0_47

Otros archivos y enlaces

Citar esto

Shang, D., Wang, Z., & Hu, Z. (2021). Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach. En X. Sun, X. Zhang, Z. Xia, & E. Bertino (Eds.), Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings: 7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I (pp. 533-565). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12736 LNCS).. https://doi.org/10.1007/978-3-030-78609-0_47

Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach. / Shang, Di (Richard); Wang, Zhaoxia; Hu, Zhenda.
Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings: 7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I. ed. / Xingming Sun; Xiaorui Zhang; Zhihua Xia; Elisa Bertino. Switzerland, 2021. p. 533-565 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12736 LNCS).

Producción científica: Literary contribution

Shang, D, Wang, Z & Hu, Z 2021, Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach. En X Sun, X Zhang, Z Xia & E Bertino (eds.), Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings: 7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12736 LNCS, Switzerland, pp. 533-565, 7th International Conference on Artificial Intelligence and Security, ICAIS 2021, Dublin, Ireland, 7/19/21. https://doi.org/10.1007/978-3-030-78609-0_47

Shang D, Wang Z, Hu Z. Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach. En Sun X, Zhang X, Xia Z, Bertino E, editores, Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings: 7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I. Switzerland. 2021. p. 533-565. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-78609-0_47

Shang, Di (Richard) ; Wang, Zhaoxia ; Hu, Zhenda. / Mining Consumer Brand Relationship from Social Media Data : A Natural Language Processing Approach. Artificial Intelligence and Security - 7th International Conference, ICAIS 2021, Proceedings: 7th International Conference, ICAIS 2021, Dublin, Ireland, July 19–23, 2021, Proceedings, Part I. editor / Xingming Sun ; Xiaorui Zhang ; Zhihua Xia ; Elisa Bertino. Switzerland, 2021. pp. 533-565 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach",

abstract = "There is a rich collection of studies exploring different aspects of consumer brand relationship. Traditional approaches of questionnaires and analysis are based on measurements collected from a relatively small number of survey participants. With the advancements in natural language processing (NLP) techniques, opportunities exist for applying NLP techniques to discover consumer brand relationship from social media platforms that possess a large amount of data on consumer opinion and sentiment. In this study, we review consumer brand relationship analysis focusing on leveraging NLP and machine learning techniques to address some challenges associated with discovering customer brand relationship from social media data and propose a methodological framework for the approach. This study has implications for both academic research and practitioners as it presents an alternative way to investigate consumer brand relationship.",

keywords = "NLP, Text mining, Consumer brand relationship, Machine Learning",

author = "Shang, {Di (Richard)} and Zhaoxia Wang and Zhenda Hu",

note = "Shang, D., Hu, Z., Wang, Z. (2021). Mining Consumer Brand Relationship from Social Media Data: A Natural Language Processing Approach. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12736. Springer, Cham. https://doi.org/10.1007/978-3-030-78609-0_47; 7th International Conference on Artificial Intelligence and Security, ICAIS 2021 ; Conference date: 19-07-2021 Through 23-07-2021",

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