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korean management review - Vol. 50 , No. 1

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[ Article ]
korean management review - Vol. 50, No. 1, pp. 115-142
Abbreviation: kmr
ISSN: 1226-1874 (Print)
Print publication date 28 Feb 2021
Received 18 Nov 2020 Revised 16 Dec 2020 Accepted 24 Dec 2020
DOI: https://doi.org/10.17287/kmr.2021.50.1.115
An Analysis on the Relationship Between Content Topics of Social Media and Customer Engagement Using Machine Learning Methodology
Jungwon Lee ; Cheol Park
(First Author) Ph.D. Candidate, Dept. of Corporate Management, Korea University (d2ljw510@naver.com)
(Corresponding Author) Professor of Global Business at Korea University Sejong (cpark@korea.ac.kr)
소셜미디어 콘텐츠 주제와 고객 인게이지먼트 간의 관계분석: 머신러닝 방법론을 중심으로

Copyright 2011 THE KOREAN ACADEMIC SOCIETY OF BUSINESS ADMINISTRATION This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Customer engagement is regarded as a performance indicator of social media marketing, and previous studies have reported that the characteristics of content to increase customer engagement. However, the topic of content has not been sufficiently studied. This study analyzes the relationship between the topic of social media content and customer engagement and suggests an analysis procedure that can apply a machine learning model, a key tool for recent digital transformation. For empirical analysis, 154,705 social media data of 51 global brands were collected, and content topics were classified using a topic modeling method. And the relationship between content topic and customer engagement was analyzed using zero-inflated negative binomial regression analysis and machine learning model. As a result of the analysis, contents of 51 brands were classified into 18 contents topics, and there was a difference in the impact on customer engagement according to the topic. In addition, using a machine learning model, it was possible to predict the customer engagement performance of the content with an accuracy of about 90%. This study contributed to the marketing literature by analyzing the relationship between social media content topics and customer engagement through machine learning methodology.


Keywords: Social media, Customer engagement, Contents marketing, Machine learning, Topic modeling, Zero-inflated negative binomial regression

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∙ The author Jungwon Lee is a Ph.D. Candidate of Corporate Management at Korea University and an Instructor at Sungsnin Women’ University and Dankook University. He received his B.B.A in International Business from Chungbuk National University and M.S in e-business from Korea University. His research interests include digital marketing, social media, machine learning, and he has published papers in Korean Management Review, Korean Marketing Review, Journal of IT Service, and Information Systems Research.

∙ The author Cheol Park is a Professor of Global Business at Korea University Sejong. He received his B.A. in Economics, M.B.A. and Ph.D. in Business Administration from Seoul National University. He had worked for Samsung as assistant manager of global marketing team before joining academic area. He has been a visiting scholar at Vanderbilt University, University of Hawaii, Mongolia International University, and University of Jinan in China. His research interests include digital marketing and online consumer behaviors. He has published papers in influential journals such as International Journal of Information Management, Journal of Interactive Marketing, International Marketing Review, and Journal of Business Research.