Short answer
Integrate automated, clear explanation systems into content moderation workflows to improve user compliance and reduce moderation load.
- Field
- User-Centred Design
- Source
- Proceedings of the ACM on Human-Computer Interaction (2019)
- Method
- Quantitative analysis of user-generated data and regression modeling.
- Sample
- 32 million Reddit posts
- Evidence
- Strong effect
Providing users with clear explanations for content moderation significantly reduces the likelihood of their future posts being removed. This user-centred design research insight is drawn from a 2019 study published in Proceedings of the ACM on Human-Computer Interaction. Using Quantitative analysis of user-generated data and regression modeling. with 32 million Reddit posts, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Integrate automated, clear explanation systems into content moderation workflows to improve user compliance and reduce moderation load.
Moderation Explanations Reduce Future Content Removals by 15%
Providing users with clear explanations for content moderation significantly reduces the likelihood of their future posts being removed.
Proceedings of the ACM on Human-Computer Interaction · 2019
Key Findings
- 01Removal explanations often educate users about community social norms.
- 02Providing explanations for content moderation reduces the odds of future post removals.
- 03Human and bot-provided explanations showed no significant difference in reducing future post removals.
Application
Design takeaway
Integrate automated, clear explanation systems into content moderation workflows to improve user compliance and reduce moderation load.
How to apply
When designing or refining moderation systems, ensure that every moderation action is accompanied by a clear, concise explanation that references specific community guidelines.
Project actions
- 01Consider how your design can provide clear feedback to users about their actions.
- 02Explore the use of automated systems for delivering feedback to improve efficiency.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Large-scale dataset provides robust statistical power.
- +Investigates a practical and under-researched aspect of online community management.
Limitations
The study's findings are specific to the context of Reddit; applying them directly to other platforms might require adaptation. The nuances of 'explanation quality' were not deeply explored.
Reliability & validity
The large sample size and quantitative methodology contribute to high reliability. Validity is supported by the direct link between explanation provision and subsequent user behavior.
Think critically
Given that bot-generated explanations were as effective as human ones, what are the ethical considerations and potential drawbacks of relying solely on automated moderation explanations?
Design Principles
"Transparency in feedback loops fosters user learning and adherence to system rules."
This research highlights the critical role of transparency in user experience within online communities. By understanding the rationale behind moderation decisions, users are better equipped to adhere to community guidelines, fostering a more positive and productive environment.
What This Means for Your Design
When you tell people why you're taking something down online, they're less likely to do it again. Bots can do this just as well as people.
How to use in your project
- 1.Use this research to justify the inclusion of clear feedback mechanisms in your design proposal, especially if your project involves user interaction or community building.
Add to My Project
Quick Cite
Paragraph starter
Research by Jhaver et al. (2019) indicates that providing clear explanations for content moderation actions significantly reduces the likelihood of future policy violations. Their analysis of millions of social media posts found that users who received explanations were less likely to have subsequent content removed, suggesting that transparency in moderation fosters user understanding and compliance. This principle can be applied to design projects by ensuring that any system involving user-generated content or rule-based interactions includes robust, informative feedback mechanisms.
Source
Proceedings of the ACM on Human-Computer Interaction
Does Transparency in Moderation Really Matter?
journal · 2019
View sourceQuestions About This Research
- What does the research say about moderation explanations reduce future content removals by 15%?
- Integrate automated, clear explanation systems into content moderation workflows to improve user compliance and reduce moderation load. Evidence: Proceedings of the ACM on Human-Computer Interaction (2019).
- Why does "Moderation Explanations Reduce Future Content Removals by 15%" matter for design?
- This research highlights the critical role of transparency in user experience within online communities. By understanding the rationale behind moderation decisions, users are better equipped to adhere to community guidelines, fostering a more positive and productive environment.
- How can designers apply this research?
- Integrate automated, clear explanation systems into content moderation workflows to improve user compliance and reduce moderation load.
- What were the main findings?
- Removal explanations often educate users about community social norms.. Providing explanations for content moderation reduces the odds of future post removals.. Human and bot-provided explanations showed no significant difference in reducing future post removals.
- What research method was used?
- Quantitative analysis of user-generated data and regression modeling. with 32 million Reddit posts.
- How strong is the evidence?
- Evidence strength is rated Strong effect, based on a 2019 journal from Proceedings of the ACM on Human-Computer Interaction.
- What should I do differently in my next project?
- When designing or refining moderation systems, ensure that every moderation action is accompanied by a clear, concise explanation that references specific community guidelines.
- What are the limitations?
- The study focused on Reddit, and findings may not generalize to all online platforms. The specific content and quality of explanations were not deeply analyzed, only their presence and type.