THE ECONOMIC VALUE OF SOCIAL MEDIA USER- AND MARKETER-GENERATED CONTENT: A NETWORK PERSPECTIVE ON CONTENT SENTIMENT AND CONTENT INFORMATION

Zhijie Lin, National University of Singapore, Singapore, Singapore.
Khim Yong Goh, National University of Singapore, Singapore, Singapore.

Abstract

Social media sites are increasingly attracting enormous interest from the public, and social relationships have substantially extended to the online context. However, prior research about impact of social media user-generated content on consumer behavior has overlooked the qualitative aspects of the contents and online social network influence. Based on the literature of social media user-generated content and online social network, this study proposes the Networked User/Marketer-Generated Content model to explore the impact of social media user-generated content and marketer-generated content on consumer purchase behavior. Individual panel-level binary logit model is employed to model consumer purchase incidence, whereas a fixed effects linear regression specification is used to model consumer purchase expenditure. This study contributes potential theoretical implications and also aims to provide helpful insights for practitioners to better understand the economic value of social media content and further design more effective marketing strategies.

 

THE ECONOMIC VALUE OF SOCIAL MEDIA USER- AND MARKETER-GENERATED CONTENT: A NETWORK PERSPECTIVE ON CONTENT SENTIMENT AND CONTENT INFORMATION

Social media sites are increasingly attracting enormous interest from the public, and social relationships have substantially extended to the online context. However, prior research about impact of social media user-generated content on consumer behavior has overlooked the qualitative aspects of the contents and online social network influence. Based on the literature of social media user-generated content and online social network, this study proposes the Networked User/Marketer-Generated Content model to explore the impact of social media user-generated content and marketer-generated content on consumer purchase behavior. Individual panel-level binary logit model is employed to model consumer purchase incidence, whereas a fixed effects linear regression specification is used to model consumer purchase expenditure. This study contributes potential theoretical implications and also aims to provide helpful insights for practitioners to better understand the economic value of social media content and further design more effective marketing strategies.