Platform design, governance, and user engagement in online communities

Abstract

To maintain the success of online communities that rely on user-generated content, platform owners must ensure a sufficient content supply, appropriate content presentation, and effective content governance. In this thesis, we focus on the impacts of novel platform designs and the use of artificial intelligence in platform governance on individual engagement behaviors. In the first study, we examine whether lowering content generation barriers by providing a new content curation channel will complement or substitute the existing high-effort content contribution in online Q&A communities. We find that the adoption of such low-barrier tool complements the contribution of existing high-effort content, possibly through increasing users’ overall engagement level on the platform. In the second study, we examine the impacts of information presentation format of various types of content on individual user’s engagement and contribution behaviors. We find that integrating information feed for different types of content (answers and ideas) into one unified feed decreased user engagement with and contribution of both types of content. Further data analysis (including an online experiment) suggests that the decrease of engagement may be explained by an information processing mechanism while the decrease of contribution can be explained both by the decreased engagement from audiences and the contributors’ social image concerns. In the third study, we investigate the impacts of algorithmic content moderation on user content generation. We find that algorithmic content moderation can work as a double-edged sword. On the one hand, it significantly inhibited users’ incentives to provide content. On the other hand, however, it increased the quality of the content and nudged users to rely more on cognitive processes while curating content, evidenced by the increased cognitive language usage in and the increased text readability of the content.

Date of Award	2023
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Yi YANG (Supervisor)