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Understanding the Prevalence of Caste: A Critical Discourse Analysis of Caste-based Marginalization on X

Despite decades of anti-caste efforts, sociocultural practices that marginalize lower-caste groups in India remain prevalent and have even proliferated with the use of social media. This paper examines how groups engaged in caste-based discrimination leverage platform aﬀordances of the social media site X (formerly Tw…

Nayana Kirasur et al.Rutgers University

Online & AI Harms

Bystanders of Online Moderation: Examining the Effects of Witnessing Post-Removal Explanations

Prior research on transparency in content moderation has demonstrated the benefits of offering post-removal explanations to sanctioned users. In this paper, we examine whether the influence of such explanations transcends those who are moderated to the bystanders who witness such explanations. We conduct a quasi-exper…

Shagun Jhaver et al.Georgia Institute of Technology

Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor

Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end users perceive the choices and affordances of different kinds of personal content m…

Shagun Jhaver et al.Georgia Institute of Technology

Moderation I

Designing Word Filter Tools for Creator-led Comment Moderation

Online social platforms centered around content creators often allow comments on content, where creators moderate the comments they receive. As creators can face overwhelming numbers of comments, with some of them harassing or hateful, platforms typically provide tools such as word filters for creators to automate asp…

Shagun Jhaver et al.Georgia Institute of Technology

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Evaluating the Effectiveness of Deplatforming as a Moderation Strategy on Twitter

Deplatforming refers to the permanent ban of controversial public figures with large followings on social media sites. In recent years, platforms like Facebook, Twitter and YouTube have deplatformed many influencers to curb the spread of offensive speech. We present a case study of three high-profile influencers who w…

Shagun Jhaver et al.Georgia Institute of Technology

Antisocial Computing

Do Platform Migrations Harm the Effectiveness of Content Moderation? Evidence from r/The_Donald and r/Incels

When toxic online communities on mainstream platforms face moderation measures, such as bans, they may migrate to other platforms with laxer policies or set up their own dedicated website. Previous work suggests that, within mainstream platforms, community-level moderation is effective in mitigating the harm caused b…

Manoel Horta Ribeiro et al.Princeton University

Antisocial Computing

Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator

What one may say on the internet is increasingly controlled by a mix of automated programs, and decisions made by paid and volunteer human moderators. On the popular social media site Reddit, moderators heavily rely on a configurable, automated program called ‘Automoderator’ (or ‘Automod’). How do moderators use Autom…

Shagun Jhaver et al.Georgia Institute of Technology

Moderation I

Learning to Airbnb by Engaging in Online Communities of Practice

Technological advances, combined with sustained, minimalist consumerism, have raised the popularity of sharing economy platforms like Airbnb and Uber. These platforms are considered to have disrupted traditional industries and revolutionized how consumers interact with their services. The Computer-Supported Cooperativ…

Maya Holikatti et al.Georgia Institute of Technology

On-demand economy

Does Transparency in Moderation Really Matter?: User Behavior After Content Removal Explanations on Reddit

When posts are removed on a social media platform, users may or may not receive an explanation. What kinds of explanations are provided? Do those explanations matter? Using a sample of 32 million Reddit posts, we characterize the removal explanations that are provided to Redditors, and link them to measures of subsequ…

Shagun Jhaver et al.Georgia Institute of Technology

Moderation I

“Did You Suspect the Post Would be Removed?”: Understanding User Reactions to Content Removals on Reddit

Thousands of users post on Reddit every day, but a fifth of all posts are removed. How do users react to these removals? We conducted a survey of 907 Reddit users, asking them to reflect on their post removal a few hours after it happened. Examining the qualitative and quantitative responses from this survey, we prese…

Shagun Jhaver et al.Georgia Institute of Technology

Moderation II

Algorithmic Anxiety and Coping Strategies of Airbnb Hosts

Algorithms increasingly mediate how work is evaluated in a wide variety of work settings. Drawing on our interviews with 15 Airbnb hosts, we explore the impact of algorithmic evaluation on users and their work practices in the context of Airbnb. Our analysis reveals that Airbnb hosts engage in a double negotiation on…

Shagun Jhaver et al.Georgia Institute of Technology

The Internet’s Hidden Rules: An Empirical Study of Reddit Norm Violations at Micro, Meso, and Macro Scales

Norms are central to how online communities are governed. Yet, norms are also emergent, arise from interaction, and can vary significantly between communities---making them challenging to study at scale. In this paper, we study community norms on Reddit in a large-scale, empirical manner. Via 2.8M comments removed by…

Eshwar Chandrasekharan et al.University of Illinois Urbana-Champaign

Norms and Rules in Online Communities

Online Harassment and Content Moderation: The Case of Blocklists

Online harassment is a complex and growing problem. On Twitter, one mechanism people use to avoid harassment is the blocklist, a list of accounts that are preemptively blocked from interacting with a subscriber. In this article, we present a rich description of Twitter blocklists – why they are needed, how they work,…

Shagun Jhaver et al.Georgia Institute of Technology

Online Harassment and Content Moderation

Paper Title	Authors	Research Topics
emoji_events Understanding the Prevalence of Caste: A Critical Discourse Analysis of Caste-based Marginalization on X Despite decades of anti-caste efforts, sociocultural practices that marginalize lower-caste groups in India remain prevalent and have even proliferated with the use of social media. This paper examines how groups engaged in caste-based discrimination leverage platform aﬀordances of the social media site X (formerly Tw…	NK Nayana Kirasur et al.Rutgers University	Online & AI Harms
Bystanders of Online Moderation: Examining the Effects of Witnessing Post-Removal Explanations Prior research on transparency in content moderation has demonstrated the benefits of offering post-removal explanations to sanctioned users. In this paper, we examine whether the influence of such explanations transcends those who are moderated to the bystanders who witness such explanations. We conduct a quasi-exper…	SJ Shagun Jhaver et al.Georgia Institute of Technology
Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end users perceive the choices and affordances of different kinds of personal content m…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Moderation I
Designing Word Filter Tools for Creator-led Comment Moderation Online social platforms centered around content creators often allow comments on content, where creators moderate the comments they receive. As creators can face overwhelming numbers of comments, with some of them harassing or hateful, platforms typically provide tools such as word filters for creators to automate asp…	SJ Shagun Jhaver et al.Georgia Institute of Technology
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
emoji_events Evaluating the Effectiveness of Deplatforming as a Moderation Strategy on Twitter Deplatforming refers to the permanent ban of controversial public figures with large followings on social media sites. In recent years, platforms like Facebook, Twitter and YouTube have deplatformed many influencers to curb the spread of offensive speech. We present a case study of three high-profile influencers who w…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Antisocial Computing
emoji_events Do Platform Migrations Harm the Effectiveness of Content Moderation? Evidence from r/The_Donald and r/Incels When toxic online communities on mainstream platforms face moderation measures, such as bans, they may migrate to other platforms with laxer policies or set up their own dedicated website. Previous work suggests that, within mainstream platforms, community-level moderation is effective in mitigating the harm caused b…	MR Manoel Horta Ribeiro et al.Princeton University	Antisocial Computing
Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator What one may say on the internet is increasingly controlled by a mix of automated programs, and decisions made by paid and volunteer human moderators. On the popular social media site Reddit, moderators heavily rely on a configurable, automated program called ‘Automoderator’ (or ‘Automod’). How do moderators use Autom…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Moderation I
Learning to Airbnb by Engaging in Online Communities of Practice Technological advances, combined with sustained, minimalist consumerism, have raised the popularity of sharing economy platforms like Airbnb and Uber. These platforms are considered to have disrupted traditional industries and revolutionized how consumers interact with their services. The Computer-Supported Cooperativ…	MH Maya Holikatti et al.Georgia Institute of Technology	On-demand economy
emoji_events Does Transparency in Moderation Really Matter?: User Behavior After Content Removal Explanations on Reddit When posts are removed on a social media platform, users may or may not receive an explanation. What kinds of explanations are provided? Do those explanations matter? Using a sample of 32 million Reddit posts, we characterize the removal explanations that are provided to Redditors, and link them to measures of subsequ…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Moderation I
emoji_events “Did You Suspect the Post Would be Removed?”: Understanding User Reactions to Content Removals on Reddit Thousands of users post on Reddit every day, but a fifth of all posts are removed. How do users react to these removals? We conducted a survey of 907 Reddit users, asking them to reflect on their post removal a few hours after it happened. Examining the qualitative and quantitative responses from this survey, we prese…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Moderation II
Algorithmic Anxiety and Coping Strategies of Airbnb Hosts Algorithms increasingly mediate how work is evaluated in a wide variety of work settings. Drawing on our interviews with 15 Airbnb hosts, we explore the impact of algorithmic evaluation on users and their work practices in the context of Airbnb. Our analysis reveals that Airbnb hosts engage in a double negotiation on…	SJ Shagun Jhaver et al.Georgia Institute of Technology
The Internet’s Hidden Rules: An Empirical Study of Reddit Norm Violations at Micro, Meso, and Macro Scales Norms are central to how online communities are governed. Yet, norms are also emergent, arise from interaction, and can vary significantly between communities---making them challenging to study at scale. In this paper, we study community norms on Reddit in a large-scale, empirical manner. Via 2.8M comments removed by…	EC Eshwar Chandrasekharan et al.University of Illinois Urbana-Champaign	Norms and Rules in Online Communities
Online Harassment and Content Moderation: The Case of Blocklists Online harassment is a complex and growing problem. On Twitter, one mechanism people use to avoid harassment is the blocklist, a list of accounts that are preemptively blocked from interacting with a subscriber. In this article, we present a rich description of Twitter blocklists – why they are needed, how they work,…	SJ Shagun Jhaver et al.Georgia Institute of Technology	Online Harassment and Content Moderation