The Design Space for Online Restorative Justice Tools: A Case Study with ApoloBot

TL;DR

This study designs and evaluates ApoloBot, a Discord-based tool embedding restorative justice principles to facilitate apologies after online harm. Through two rounds of moderator interviews (n=16) and a four-week deployment with a subset of participants, the authors map an opportunity space across community context, moderation practices, and-case scenarios, while identifying challenges such as contextual ambiguity, stakeholder dropout, and distrust toward automated tools. The findings inform design implications for future RJ tools, including richer stakeholder interaction, transparency, education, and potential pre/post-harm extensions, highlighting the nuanced trade-offs between efficiency and restorative depth. The work offers a concrete, adaptable blueprint for integrating restorative practices into online communities and outlines metrics and methodologies for evaluating restorative outcomes in socio-technical systems.

Abstract

Volunteer moderators use various strategies to address online harms within their communities. Although punitive measures like content removal or account bans are common, recent research has explored the potential for restorative justice as an alternative framework to address the distinct needs of victims, offenders, and community members. In this study, we take steps toward identifying a more concrete design space for restorative justice-oriented tools by developing ApoloBot, a Discord bot designed to facilitate apologies when harm occurs in online communities. We present results from two rounds of interviews: first, with moderators giving feedback about the design of ApoloBot, and second, after a subset of these moderators have deployed ApoloBot in their communities. This study builds on prior work to yield more detailed insights regarding the potential of adopting online restorative justice tools, including opportunities, challenges, and implications for future designs.

Figures (4)

• Figure 1: The slash command /apolomute that is used in the primary workflow. The first four input fields are required, where the moderator specifies the involved offender and victim, along with mute duration and reason. Optionally, proof can be attached as an image, and moderator can choose to first review the victim's apology request by setting 'review-request' to True.
• Figure 2: ApoloBot's Primary Workflow. The diagram shows the different pathways ApoloBot can follow based on stakeholders' decisions to approve or decline their actions. The green blocks represent the interaction points for the moderator, who keeps up with ApoloBot through their log channels. The blue and red ones depict the interaction for the victim and the offender, respectively, in their private threads. Yellow blocks indicate the case is closed and no further steps will be taken.
• Figure 3: Examples of private threads ApoloBot created from the victim's side and the offender's side.
• Figure 4: Examples of ApoloBot logs received by moderators.