Abstract
Social media platforms want to increase their valuation in terms of total content quantity and user engagement. Monetization is often used to induce user content generation. However, research documents that while monetization increases the quantity of specific kinds of content, it does not necessarily increase the total content quantity or user engagement (i.e., platform value). Furthermore, the impact of monetization may depend on the social status of content creators. This article investigates paid question and answer (paid Q&A). Based on expectancy theory and relevant research, this article hypothesizes the effects of introducing paid Q&A on both total content quantity and user engagement and on answerers of differing statuses. We test the model using data from a natural quasi-experiment of the introduction of paid Q&A to Weibo. The key insight of our study is that total platform value in terms of both total content quantity and user engagement rises with the presence of paid Q&A. Furthermore, we find that an answerer's status negatively moderates the impact of introducing the paid Q&A feature on total content quantity but positively moderates its impact on user engagement. Our research provides insights into the causality of introducing the paid Q&A feature on platform value as well as the boundary condition of this relationship. Practically, paid Q&A is shown to be profitable to social media platforms and to increase the benefits to platform users.
Recommended Citation
Ye, J. H., & Chua, C. E. (2022). Monetization for Content Generation and User Engagement on Social Media Platforms: Evidence from Paid Q&a. IEEE Transactions on Engineering Management Institute of Electrical and Electronics Engineers.
The definitive version is available at https://doi.org/10.1109/TEM.2022.3209534
Department(s)
Business and Information Technology
Keywords and Phrases
Behavioral sciences; Business; Engagement; Media; monetization; paid Q&A; platform valuation; Production; Shape; Social networking (online); status seeking; Task analysis; total content quantity
International Standard Serial Number (ISSN)
1558-0040; 0018-9391
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2023 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2022
