Analyzing the Online Word of Mouth Dynamics: A Novel Approach

Posted: 6 Sep 2023

See all articles by Xian Cao

Xian Cao

Ball State University

Timothy Folta

University of Connecticut - Department of Management

Hongfei Li

Chinese University of Hong Kong

Ruoqing Zhu

University of Illinois at Urbana-Champaign

Date Written: August 25, 2023

Abstract

Nowadays, nearly all products and services generate WOM on social media but at least three challenges hinder the analysis of online WOM. First, WOM is usually unstructured data in various forms. However, the process of transforming unstructured data can generate many variables, increasing the need for dimension reduction. Second, WOM can be continuous or bursty, and it may change dramatically in a short period. Third, important events might trigger symmetric or asymmetric reactions in WOM across rivals. We introduce a new computationally efficient method—multi-view sequential canonical covariance analysis to solve these methodological challenges. This method attempts to solve the myriad WOM conversational dimensions, detect WOM dynamic trends, and examine the shared WOM across rivals. We illustrate the advantages of this new method using two empirical examples. This new method provides a novel insight into the online WOM dynamics and can contribute to a wide range of fields.

Keywords: Multi-view sequential canonical covariance analysis, canonical correlation analysis, online word-of-mouth dynamics, dimension reduction, social media

Suggested Citation

Cao, Xian and Folta, Timothy and Li, Hongfei and Zhu, Ruoqing, Analyzing the Online Word of Mouth Dynamics: A Novel Approach (August 25, 2023). Available at SSRN: https://ssrn.com/abstract=4561596

Xian Cao

Ball State University ( email )

Muncie, IN 47306-0340
United States

Timothy Folta

University of Connecticut - Department of Management ( email )

Storrs, CT 06269-1041
United States

Hongfei Li (Contact Author)

Chinese University of Hong Kong

39439679 (Phone)
999077 (Fax)

HOME PAGE: http://www.bschool.cuhk.edu.hk/staff/li-hongfei/

Ruoqing Zhu

University of Illinois at Urbana-Champaign ( email )

Urbana, IL Champaign 61801
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
64
PlumX Metrics