skip to main content


The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 10:00 PM ET on Friday, December 8 until 2:00 AM ET on Saturday, December 9 due to maintenance. We apologize for the inconvenience.

Title: Proactive Moderation of Online Discussions: Existing Practices and the Potential for Algorithmic Support
To address the widespread problem of uncivil behavior, many online discussion platforms employ human moderators to take action against objectionable content, such as removing it or placing sanctions on its authors. Thisreactive paradigm of taking action against already-posted antisocial content is currently the most common form of moderation, and has accordingly underpinned many recent efforts at introducing automation into the moderation process. Comparatively less work has been done to understand other moderation paradigms---such as proactively discouraging the emergence of antisocial behavior rather than reacting to it---and the role algorithmic support can play in these paradigms. In this work, we investigate such a proactive framework for moderation in a case study of a collaborative setting: Wikipedia Talk Pages. We employ a mixed methods approach, combining qualitative and design components for a holistic analysis. Through interviews with moderators, we find that despite a lack of technical and social support, moderators already engage in a number of proactive moderation behaviors, such as preemptively intervening in conversations to keep them on track. Further, we explore how automation could assist with this existing proactive moderation workflow by building a prototype tool, presenting it to moderators, and examining how the assistance it provides might fit into their workflow. The resulting feedback uncovers both strengths and drawbacks of the prototype tool and suggests concrete steps towards further developing such assisting technology so it can most effectively support moderators in their existing proactive moderation workflow.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Proceedings of the ACM on Human-Computer Interaction
Page Range / eLocation ID:
1 to 27
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Past work has explored various ways for online platforms to leverage crowd wisdom for misinformation detection and moderation. Yet, platforms often relegate governance to their communities, and limited research has been done from the perspective of these communities and their moderators. How is misinformation currently moderated in online communities that are heavily self-governed? What role does the crowd play in this process, and how can this process be improved? In this study, we answer these questions through semi-structured interviews with Reddit moderators. We focus on a case study of COVID-19 misinformation. First, our analysis identifies a general moderation workflow model encompassing various processes participants use for handling COVID-19 misinformation. Further, we show that the moderation workflow revolves around three elements: content facticity, user intent, and perceived harm. Next, our interviews reveal that Reddit moderators rely on two types of crowd wisdom for misinformation detection. Almost all participants are heavily reliant on reports from crowds of ordinary users to identify potential misinformation. A second crowd--participants' own moderation teams and expert moderators of other communities--provide support when participants encounter difficult, ambiguous cases. Finally, we use design probes to better understand how different types of crowd signals---from ordinary users and moderators---readily available on Reddit can assist moderators with identifying misinformation. We observe that nearly half of all participants preferred these cues over labels from expert fact-checkers because these cues can help them discern user intent. Additionally, a quarter of the participants distrust professional fact-checkers, raising important concerns about misinformation moderation. 
    more » « less
  2. Incivility remains a major challenge for online discussion platforms, to such an extent that even conversations between well-intentioned users can often derail into uncivil behavior. Traditionally, platforms have relied on moderators to---with or without algorithmic assistance---take corrective actions such as removing comments or banning users. In this work we propose a complementary paradigm that directly empowers users by proactively enhancing their awareness about existing tension in the conversation they are engaging in and actively guides them as they are drafting their replies to avoid further escalation. As a proof of concept for this paradigm, we design an algorithmic tool that provides such proactive information directly to users, and conduct a user study in a popular discussion platform. Through a mixed methods approach combining surveys with a randomized controlled experiment, we uncover qualitative and quantitative insights regarding how the participants utilize and react to this information. Most participants report finding this proactive paradigm valuable, noting that it helps them to identify tension that they may have otherwise missed and prompts them to further reflect on their own replies and to revise them. These effects are corroborated by a comparison of how the participants draft their reply when our tool warns them that their conversation is at risk of derailing into uncivil behavior versus in a control condition where the tool is disabled.These preliminary findings highlight the potential of this user-centered paradigm and point to concrete directions for future implementations. 
    more » « less
  3. Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and moderation, which is often supported by volunteer efforts. Moderation, as a non-technical form of labor, is a necessary but often overlooked task that maintainers undertake to sustain the community around an OSS project. This study examines the various structures and norms that support community moderation, describes the strategies moderators use to mitigate conflicts, and assesses how bots can play a role in assisting these processes. We interviewed 14 practitioners to uncover existing moderation practices and ways that automation can provide assistance. Our main contributions include a characterization of moderated content in OSS projects, moderation techniques, as well as perceptions of and recommendations for improving the automation of moderation tasks. We hope that these findings will inform the implementation of more effective moderation practices in open source communities.

    more » « less
  4. Moderators of online communities often employ comment deletion as a tool. We ask here whether, beyond the positive effects of shielding a community from undesirable content, does comment removal actually cause the behavior of the comment’s author to improve? We examine this question in a particularly well-moderated community, the ChangeMyView subreddit. The standard analytic approach of interrupted time-series analysis unfortunately cannot answer this question of causality because it fails to distinguish the effect of having made a non-compliant comment from the effect of being subjected to moderator removal of that comment. We therefore leverage a “delayed feedback” approach based on the observation that some users may remain active between the time when they posted the non-compliant comment and the time when that comment is deleted. Applying this approach to such users, we reveal the causal role of comment deletion in reducing immediate noncompliance rates, although we do not find evidence of it having a causal role in inducing other behavior improvements. Our work thus empirically demonstrates both the promise and some potential limits of content removal as a positive moderation strategy, and points to future directions for identifying causal effects from observational data. 
    more » « less
  5. This Article develops a framework for both assessing and designing content moderation systems consistent with public values. It argues that moderation should not be understood as a single function, but as a set of subfunctions common to all content governance regimes. By identifying the particular values implicated by each of these subfunctions, it explores the appropriate ways the constituent tasks might best be allocated-specifically to which actors (public or private, human or technological) they might be assigned, and what constraints or processes might be required in their performance. This analysis can facilitate the evaluation and design of content moderation systems to ensure the capacity and competencies necessary for legitimate, distributed systems of content governance. Through a combination of methods, legal schemes delegate at least a portion of the responsibility for governing online expression to private actors. Sometimes, statutory schemes assign regulatory tasks explicitly. In others, this delegation often occurs implicitly, with little guidance as to how the treatment of content should be structured. In the law's shadow, online platforms are largely given free rein to configure the governance of expression. Legal scholarship has surfaced important concerns about the private sector's role in content governance. In response, private platforms engaged in content moderation have adopted structures that mimic public governance forms. Yet, we largely lack the means to measure whether these forms are substantive, effectively infusing public values into the content moderation process, or merely symbolic artifice designed to deflect much needed public scrutiny. This Article's proposed framework addresses that gap in two ways. First, the framework considers together all manner of legal regimes that induce platforms to engage in the function of content moderation. Second, it focuses on the shared set of specific tasks, or subfunctions, involved in the content moderation function across these regimes. Examining a broad range of content moderation regimes together highlights the existence of distinct common tasks and decision points that together constitute the content moderation function. Focusing on this shared set of subfunctions highlights the different values implicated by each and the way they can be "handed off' to human and technical actors to perform in different ways with varying normative and political implications. This Article identifies four key content moderation subfunctions: (1) definition of policies, (2) identification of potentially covered content, (3) application of policies to specific cases, and (4) resolution of those cases. Using these four subfunctions supports a rigorous analysis of how to leverage the capacities and competencies of government and private parties throughout the content moderation process. Such attention also highlights how the exercise of that power can be constrained-either by requiring the use of particular decision-making processes or through limits on the use of automation-in ways that further address normative concerns. Dissecting the allocation of subfunctions in various content moderation regimes reveals the distinct ethical and political questions that arise in alternate configurations. Specifically, it offers a way to think about four key questions: (1) what values are most at issue regarding each subfunction; (2) which activities might be more appropriate to delegate to particular public or private actors; (3) which constraints must be attached to the delegation of each subfunction; and (4) where can investments in shared content moderation infrastructures support relevant values? The functional framework thus provides a means for both evaluating the symbolic legal forms that firms have constructed in service of content moderation and for designing processes that better reflect public values. 
    more » « less