How Community Feedback Shapes User Behavior
Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jure Leskovec

TL;DR
This study examines how social media feedback influences user behavior, revealing that negative ratings decrease content quality and community cohesion, while positive feedback has limited effects, highlighting the complex social dynamics of online communities.
Contribution
It provides empirical evidence on how negative feedback impacts user behavior and community health, a novel analysis of feedback effects in large comment-based news communities.
Findings
Negative feedback reduces content quality and increases negative evaluations.
Authors receiving no feedback are most likely to leave the community.
Equal positive and negative votes lead to community polarization.
Abstract
Social media systems rely on user feedback and rating mechanisms for personalization, ranking, and content filtering. However, when users evaluate content contributed by fellow users (e.g., by liking a post or voting on a comment), these evaluations create complex social feedback effects. This paper investigates how ratings on a piece of content affect its author's future behavior. By studying four large comment-based news communities, we find that negative feedback leads to significant behavioral changes that are detrimental to the community. Not only do authors of negatively-evaluated content contribute more, but also their future posts are of lower quality, and are perceived by the community as such. Moreover, these authors are more likely to subsequently evaluate their fellow users negatively, percolating these effects through the community. In contrast, positive feedback does not…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOpinion Dynamics and Social Influence · Spam and Phishing Detection · Social Media and Politics
