Big Data Analytics for Marketing Strategy

Jingying Liang; Yuhan Jiao; Sui Ying Chung; C. K.M. Lee

Big Data Analytics for Marketing Strategy

Jingying Liang, Yuhan Jiao, Sui Ying Chung, C. K.M. Lee

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

The advent of advanced information and communication technologies have boosted the customer-brand interactions. This study utilizes big data in investigating how social media activities affect customer engagement in brand communities. As initial criteria to evaluate subscribers’ emotional reactions, we used the Feedback Ratio and the Gross Positive Feedback Ratio. A web crawler was then applied to obtain data-driven insights on real-time emotions and behaviors of customer engagement on social media using data containing 4.39 hundred million video comments and the “likes” captured from the top 12 YouTubers in various fields. The results indicate that social media marketing activities help improve customer engagement within brand communities. This paper also examines how brands may encourage long-term customer relationships through social networks.

Original language	English
Title of host publication	International Conference on Design and Semantics of Form and Movement
Editors	Miguel Bruns, Lin-Lin Chen, Jun Hu, Sara Colombo, Yihyun Lim, Steven Kyffin, Ozcan Vieira, E. Jeroen Raijmakers, Lucia Rampino, Edgar Rodriguez Ramirez, Dagmar Johanna Steffen, Calvin Wong
Publisher	The Hong Kong Polytechnic University, Hong Kong
Pages	77-86
Number of pages	10
ISBN (Print)	9789623678704
Publication status	Published - Jul 2023
Event	12th International Conference on Design and Semantics of Form and Movement, DeSForM 2023 - Hong Kong, Hong Kong Duration: 5 Jul 2023 → 7 Jul 2023

Publication series

Name	International Conference on Design and Semantics of Form and Movement
ISSN (Electronic)	2706-6150

Conference

Conference	12th International Conference on Design and Semantics of Form and Movement, DeSForM 2023
Country/Territory	Hong Kong
City	Hong Kong
Period	5/07/23 → 7/07/23

Keywords

amazing
awesome
Best
Big data Analytics
Brand Communities
Customer Engagement
down
glad Hate
good
great
like
love
Sentiment Analysis
shit
sick
wow
wrong

ASJC Scopus subject areas

Arts and Humanities (miscellaneous)
Human-Computer Interaction
Mechanics of Materials

Cite this

Liang, J., Jiao, Y., Chung, S. Y., & Lee, C. K. M. (2023). Big Data Analytics for Marketing Strategy. In M. Bruns, L.-L. Chen, J. Hu, S. Colombo, Y. Lim, S. Kyffin, O. Vieira, E. J. Raijmakers, L. Rampino, E. R. Ramirez, D. J. Steffen, & C. Wong (Eds.), International Conference on Design and Semantics of Form and Movement (pp. 77-86). (International Conference on Design and Semantics of Form and Movement). The Hong Kong Polytechnic University, Hong Kong.

Liang, Jingying ; Jiao, Yuhan ; Chung, Sui Ying et al. / Big Data Analytics for Marketing Strategy. International Conference on Design and Semantics of Form and Movement. editor / Miguel Bruns ; Lin-Lin Chen ; Jun Hu ; Sara Colombo ; Yihyun Lim ; Steven Kyffin ; Ozcan Vieira ; E. Jeroen Raijmakers ; Lucia Rampino ; Edgar Rodriguez Ramirez ; Dagmar Johanna Steffen ; Calvin Wong. The Hong Kong Polytechnic University, Hong Kong, 2023. pp. 77-86 (International Conference on Design and Semantics of Form and Movement).

@inproceedings{f976dc8cddde4631b7c994db39aa2d22,

title = "Big Data Analytics for Marketing Strategy",

abstract = "The advent of advanced information and communication technologies have boosted the customer-brand interactions. This study utilizes big data in investigating how social media activities affect customer engagement in brand communities. As initial criteria to evaluate subscribers{\textquoteright} emotional reactions, we used the Feedback Ratio and the Gross Positive Feedback Ratio. A web crawler was then applied to obtain data-driven insights on real-time emotions and behaviors of customer engagement on social media using data containing 4.39 hundred million video comments and the “likes” captured from the top 12 YouTubers in various fields. The results indicate that social media marketing activities help improve customer engagement within brand communities. This paper also examines how brands may encourage long-term customer relationships through social networks.",

keywords = "amazing, awesome, Best, Big data Analytics, Brand Communities, Customer Engagement, down, glad Hate, good, great, like, love, Sentiment Analysis, shit, sick, wow, wrong",

author = "Jingying Liang and Yuhan Jiao and Chung, {Sui Ying} and Lee, {C. K.M.}",

note = "Publisher Copyright: {\textcopyright} 2023, The Hong Kong Polytechnic University. All rights reserved.; 12th International Conference on Design and Semantics of Form and Movement, DeSForM 2023 ; Conference date: 05-07-2023 Through 07-07-2023",

year = "2023",

month = jul,

language = "English",

isbn = "9789623678704",

series = "International Conference on Design and Semantics of Form and Movement",

publisher = "The Hong Kong Polytechnic University, Hong Kong",

pages = "77--86",

editor = "Miguel Bruns and Lin-Lin Chen and Jun Hu and Sara Colombo and Yihyun Lim and Steven Kyffin and Ozcan Vieira and Raijmakers, {E. Jeroen} and Lucia Rampino and Ramirez, {Edgar Rodriguez} and Steffen, {Dagmar Johanna} and Calvin Wong",

booktitle = "International Conference on Design and Semantics of Form and Movement",

}

Liang, J, Jiao, Y, Chung, SY & Lee, CKM 2023, Big Data Analytics for Marketing Strategy. in M Bruns, L-L Chen, J Hu, S Colombo, Y Lim, S Kyffin, O Vieira, EJ Raijmakers, L Rampino, ER Ramirez, DJ Steffen & C Wong (eds), International Conference on Design and Semantics of Form and Movement. International Conference on Design and Semantics of Form and Movement, The Hong Kong Polytechnic University, Hong Kong, pp. 77-86, 12th International Conference on Design and Semantics of Form and Movement, DeSForM 2023, Hong Kong, Hong Kong, 5/07/23.

Big Data Analytics for Marketing Strategy. / Liang, Jingying; Jiao, Yuhan; Chung, Sui Ying et al.
International Conference on Design and Semantics of Form and Movement. ed. / Miguel Bruns; Lin-Lin Chen; Jun Hu; Sara Colombo; Yihyun Lim; Steven Kyffin; Ozcan Vieira; E. Jeroen Raijmakers; Lucia Rampino; Edgar Rodriguez Ramirez; Dagmar Johanna Steffen; Calvin Wong. The Hong Kong Polytechnic University, Hong Kong, 2023. p. 77-86 (International Conference on Design and Semantics of Form and Movement).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Big Data Analytics for Marketing Strategy

AU - Liang, Jingying

AU - Jiao, Yuhan

AU - Chung, Sui Ying

AU - Lee, C. K.M.

PY - 2023/7

Y1 - 2023/7

N2 - The advent of advanced information and communication technologies have boosted the customer-brand interactions. This study utilizes big data in investigating how social media activities affect customer engagement in brand communities. As initial criteria to evaluate subscribers’ emotional reactions, we used the Feedback Ratio and the Gross Positive Feedback Ratio. A web crawler was then applied to obtain data-driven insights on real-time emotions and behaviors of customer engagement on social media using data containing 4.39 hundred million video comments and the “likes” captured from the top 12 YouTubers in various fields. The results indicate that social media marketing activities help improve customer engagement within brand communities. This paper also examines how brands may encourage long-term customer relationships through social networks.

AB - The advent of advanced information and communication technologies have boosted the customer-brand interactions. This study utilizes big data in investigating how social media activities affect customer engagement in brand communities. As initial criteria to evaluate subscribers’ emotional reactions, we used the Feedback Ratio and the Gross Positive Feedback Ratio. A web crawler was then applied to obtain data-driven insights on real-time emotions and behaviors of customer engagement on social media using data containing 4.39 hundred million video comments and the “likes” captured from the top 12 YouTubers in various fields. The results indicate that social media marketing activities help improve customer engagement within brand communities. This paper also examines how brands may encourage long-term customer relationships through social networks.

KW - amazing

KW - awesome

KW - Best

KW - Big data Analytics

KW - Brand Communities

KW - Customer Engagement

KW - down

KW - glad Hate

KW - good

KW - great

KW - like

KW - love

KW - Sentiment Analysis

KW - shit

KW - sick

KW - wow

KW - wrong

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M3 - Conference article published in proceeding or book

AN - SCOPUS:85190707658

SN - 9789623678704

T3 - International Conference on Design and Semantics of Form and Movement

SP - 77

EP - 86

BT - International Conference on Design and Semantics of Form and Movement

A2 - Bruns, Miguel

A2 - Chen, Lin-Lin

A2 - Hu, Jun

A2 - Colombo, Sara

A2 - Lim, Yihyun

A2 - Kyffin, Steven

A2 - Vieira, Ozcan

A2 - Raijmakers, E. Jeroen

A2 - Rampino, Lucia

A2 - Ramirez, Edgar Rodriguez

A2 - Steffen, Dagmar Johanna

A2 - Wong, Calvin

PB - The Hong Kong Polytechnic University, Hong Kong

T2 - 12th International Conference on Design and Semantics of Form and Movement, DeSForM 2023

Y2 - 5 July 2023 through 7 July 2023

ER -

Liang J, Jiao Y, Chung SY, Lee CKM. Big Data Analytics for Marketing Strategy. In Bruns M, Chen LL, Hu J, Colombo S, Lim Y, Kyffin S, Vieira O, Raijmakers EJ, Rampino L, Ramirez ER, Steffen DJ, Wong C, editors, International Conference on Design and Semantics of Form and Movement. The Hong Kong Polytechnic University, Hong Kong. 2023. p. 77-86. (International Conference on Design and Semantics of Form and Movement).

Big Data Analytics for Marketing Strategy

Abstract

Publication series

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Keywords

ASJC Scopus subject areas

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