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The Pin of Shame: Examining Content Creators' Adoption of Pinning Inappropriate Comments as a Moderation Strategy

T0 review · 2 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read Creators pin offensive comments to shame the commenters

desk verdict A genuinely new empirical finding about a creator-led moderation tactic, with a real sampling-bias asterisk that the paper itself never fully owns. read the letter →

arxiv 2505.14844 v2 pith:JQ7L2GV7 submitted 2025-05-20 cs.HC

Yunhee Shim , Shagun Jhaver This is my paper
classification cs.HC
keywords PinofShamecommentpinningcontentmoderationpublicshamingcreatorsonlineharassmentnormenforcementsocialmediaplatforms
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that content creators are re-purposing social media's comment-pinning feature into a deliberate moderation tactic: pinning a norm-violating comment to the top of the thread so the audience will see it and shame the commenter. Based on interviews with 20 creators who had pinned negative comments, the authors identify four motivations: punishing and educating the offender, eliciting emotional accountability, provoking audience negotiation of community norms, and managing the creator's public impression. They find the tactic yields emotional relief, social support, and a sense of empowerment, while also carrying risks of emotional strain and escalation into networked harassment. The authors use these findings to argue that moderation design should support emotional accountability, transparency, norm negotiation, and emotion-sensitive algorithms rather than visibility-reduction alone. If the paper is right, comment pinning is not a neutral display feature but a mechanism of collective norm enforcement that platforms currently neither design for nor govern.

What carries the argument

The central object is the Pin of Shame itself: the repurposing of the comment-pinning affordance, which fixes one comment at the top of a thread regardless of later activity or sorting order, so that it maximally exposes a norm-violating comment and invites collective shaming. The mechanism is visibility as sanction: instead of deleting or hiding the offending comment, the creator amplifies it, transforming the comments section into a discursive arena where the audience criticizes, counters, and negotiates norms. This inversion of the platform's usual visibility-reduction punishment logic is what carries the argument, supported by semi-structured interviews and thematic analysis of 20 creators across Instagram and YouTube.

What would settle it

A large-scale observational study could test the shaming mechanism directly: if threads where creators pin negative comments do not receive measurably more critical or shaming replies than equally visible unpinned negative comments, the claimed mechanism of mobilizing audience shaming would fail. A second check would compare apology, deletion, and repeat-offense rates of pinned commenters against commenters sanctioned by removal; if pinned commenters show no behavioral change, the paper's educational and accountability claims would not hold.

Watch

Extended reading notes

Core claim

The paper's central claim is that the Pin of Shame is an emergent, creator-led moderation strategy in which a creator intentionally fixes an inappropriate comment at the top of the comments section to expose it to public scrutiny and provoke shaming responses. Interview analysis shows creators deploy it to punish and educate the commenter, to hold the commenter emotionally accountable in a visible way, to let their audience negotiate what counts as a norm violation, and to support their own impression-management goals. Creators report that the practice validates their emotional responses, reduces the cognitive labor of responding alone, provides social support, and preserves free speech and documentation value by keeping the comment visible. The paper also documents negative consequences: stress from exposure to persistent negativity, worry when the pinned comment attracts support, and derailment into insults or networked harassment. The authors position the practice as inverting platforms' usual logic of punishing by hiding, and as evidence that moderation tools should aim for emotional accountability and transparent, participatory norm-setting.

Load-bearing premise

The paper's account rests on 20 interviews with creators recruited partly through keyword searches like 'PinofShame,' 'LGBTQ,' 'MAGA,' and 'WomeninMaleFields'; if that recruitment mostly captured creators who already identify with the label and post about politically heated topics, the motivations and outcomes described may not represent creators who pin negative comments without using the term.

Editorial extensions

If this is right

  • Platforms that offer comment pinning are currently hosting a moderation practice they did not design for; the paper implies that default pinning features should be paired with safeguards, such as early derailment detection and prompts that let pinned commenters edit or remove their comment.
  • Creator-led moderation research should treat emotional accountability, having the harm acknowledged and the violator face consequences in view of the community, as a distinct goal from content removal.
  • The common belief among creators that negative engagement boosts algorithmic promotion means recommendation systems should use emotion-sensitive engagement metrics and communicate how they work.
  • Because the Pin of Shame keeps the offending comment visible, it offers transparency that removal-based moderation lacks, which can improve observers' perceptions of fairness and support norm education.
  • The Pin of Shame makes visible the fact that community norms are negotiated, not fixed, and it can serve as a catalyst for collective debate over what counts as inappropriate.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • A natural test of the paper's account would be a large-scale observational study comparing threads where creators pin negative comments with threads where equally negative comments are unpinned; if pinned comments do not receive disproportionately more critical replies, the shaming mechanism is not doing the work the interviewees describe.
  • The paper interviews only instigators; the missing perspective of pinned commenters leaves open whether the tactic actually educates or deters them, or instead entrenches hostility and fuels more harassment.
  • Platforms could treat the Pin of Shame as a signal in moderation systems, for example by automatically offering the pinned commenter a chance to edit or retract before a thread escalates, which would extend the paper's design recommendations into deployable features.
  • The paper's finding about creators' folk theories of algorithm amplification suggests a testable hypothesis: if creators believe controversy boosts reach, they may pin comments more often on posts they want to promote, which could be examined by correlating pinning behavior with creators' stated promotion goals.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. This paper reports a qualitative interview study (N=20) with content creators who use the 'Pin of Shame'—pinning a norm-violating comment to the top of their comments section to invite public shaming. Through thematic analysis, the authors identify motivations (norm education, shaping what counts as a norm violation, engagement and content promotion, immediate low-effort action), consequences (holding violators accountable, emotional empowerment and social support, saving cognitive effort, preserving free speech, impression management, and emotional stress), and compare the tactic with other moderation tools. The paper argues that the practice offers benefits and risks and derives design implications for moderation tools, including emotional accountability, impression management support, and emotion-sensitive recommender systems.

Significance. If the empirical claims hold, this is a timely and valuable contribution to HCI/CSCW research on creator-led moderation, extending prior work on blocklists, word filters, and flagging with a nuanced account of a visibility-increasing moderation tactic. The paper's strengths include the detailed interview data with direct quotes, the explicit procedural comparison of the Pin of Shame with other moderation affordances, and the balanced treatment of both benefits and harms. The design implications in Section 5 are clearly connected to the findings. However, the study's sampling strategy limits the generalizability of the thematic characterization, and the paper currently overstates the scope of its claims without adequate acknowledgment of this limitation.

major comments (2)
  1. [3.1] The purposive sampling strategy is doubly selective: candidates were identified through keyword searches for politically charged topics and the hashtag 'PinofShame,' and then further curated by liking and bookmarking relevant posts to trigger platform recommendations. Of 239 identified candidates, only 20 were interviewed; the paper reports no response rate, no reasons for non-participation, and no comparison with creators who pin negative comments without using the term 'Pin of Shame.' Because the interviews repeatedly use this label and focus on its motivations and outcomes, the themes in Section 4 may reflect the experiences of a self-selected subset of creators who are already invested in public shaming as a strategy. Please either (a) reframe the claims throughout Sections 4 and 5 as specific to this subset, or (b) provide additional evidence (e.g., a comparison group, or a justification that the sampling logic captures the full range of pinning-for-moderation practices).
  2. [1, 5] The paper repeatedly asserts that the Pin of Shame is 'prevalent' (Section 1) and draws general conclusions about 'content creators' (e.g., the Abstract sentence 'creators adopt the Pin of Shame to punish and educate,' and Section 5.2's 'the Pin of Shame emerges as a unique tool that satisfies content creators' desire'). Yet no prevalence data are presented, and the sample is not representative of all creators who pin negative comments. These overgeneralized statements go beyond the evidence and should be tempered, e.g., by stating that the findings characterize the experiences of the interviewed creators and the subset they represent; the limitations section (5.7) should also explicitly disclose the recruitment-related selection bias.
minor comments (5)
  1. [3.3] The data analysis section reports 98 initial codes, then '12 parent codes and 76 child codes' (a total of 88); please clarify how the remaining codes were consolidated or dropped.
  2. [1, Table 1] The definition of 'content creators' in Section 1 as 'actively posting social media users with a large number of followers' conflicts with Table 1, which includes participants with 500-1k followers; please align the definition with the sample or explain the inclusion criterion.
  3. [4.2.6, 5.1] The Discussion states that the Pin of Shame 'can occasionally devolve into doxxing or personal insults,' but the supporting excerpt in Section 4.2.6 (P4) illustrates personal insults without explicit mention of doxxing; please clarify whether doxxing appeared in the interviews or is an interpretive extension.
  4. [1] There are several typographical and formatting issues: 'availabililty' in Section 1, a stray space before the comma in the Jayan quote ('not Indian , '), and inconsistent spacing after quoted keyword strings such as 'LGBTQ, ' and 'MAGA'.
  5. [3.1] The statement that 'our conversations with participants suggest that the Pin of Shame phenomenon occurs with notable frequency' is used as a justification for platform selection, but this is a post-hoc observation from the sample itself; it should be presented as a finding or moved to the limitations discussion.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: interview-derived themes are grounded in external data and not entailed by the recruitment definition.

full rationale

The paper's central claims are qualitative findings drawn from semi-structured interviews with 20 content creators, and they are supported by quoted participant accounts (Sections 4.1-4.2). The definition of 'Pin of Shame' (Section 1: 'creators intentionally pin norm-violating comments to spotlight them and prompt shaming responses') overlaps with the recruitment criterion, so the finding that the tactic is used to invite shaming is partly built into the sample. However, the specific reported motivations and consequences—norm education, emotional accountability, impression management, free-speech rationales, and emotional strain—are not entailed by the definition or by the hashtag used for recruitment. The recruitment strategy described in Section 3.1, including use of the keyword 'PinofShame' and politically charged terms, is a sampling and generalizability limitation, not a circular derivation: the interview excerpts are external evidence, and no fitted parameter or formal prediction is being renamed as a result. The paper's own Section 5.7 acknowledges scope limits by noting that only deploying creators were interviewed. Self-citations (e.g., [47], [49], [102], [115]) are background literature and are not load-bearing for the central empirical claim. There is no uniqueness theorem, no imported ansatz, and no equation-level equivalence between inputs and outputs. The absence of prevalence data and the lack of a comparison group are correctness or generalizability concerns, not circularity.

Assumptions & free parameters 0 free parameters · 4 assumptions · 1 invented entities

The study's claims rest on interview self-reports and a purposive sample recruited via keyword searches; these are domain assumptions rather than freely fitted parameters. No numeric constants are fit.

assumptions (4)
  • domain assumption Interview self-reports are treated as valid evidence of creators' motivations and perceived outcomes.
    The findings rest on retrospective verbal accounts (Section 3.2), which may be subject to social desirability and post-hoc rationalization; no behavioral verification is provided.
  • domain assumption The purposive sampling strategy via keyword searches and platform recommendations yields a representative range of 'Pin of Shame' users.
    Section 3.1: candidates were found through keywords such as 'PinofShame', 'LGBTQ', 'MAGA' and liked/bookmarked posts; this may bias the sample toward users who embrace the term and toward controversial topics.
  • domain assumption Thematic analysis saturation after 15 interviews, plus five confirmatory interviews, indicates coverage of the major themes.
    Section 3.2: saturation is asserted without showing code saturation curves or negative case analysis; five extra interviews may not add new themes but saturation is not demonstrated.
  • domain assumption Participants' descriptions of audience responses (e.g., apologies, comment deletion, shaming replies) accurately reflect what occurred.
    Section 4.2: outcome claims such as 'the pinned commenters sometimes delete the comment or apologize' rely on creators' accounts; the researchers did not independently observe all instances.
invented entities (1)
  • Pin of Shame as a named strategy independent evidence
    purpose: Labels the practice of pinning a negative comment to invite audience shaming, framing it as a moderation strategy for analysis.
    The paper documents real Instagram examples (Figure 1) and 20 interview participants who report using the tactic, so the label has external referents; the term itself is colloquial and pre-existing, not invented solely for the paper.

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Cite this review

Pith. "Pith review of The Pin of Shame: Examining Content Creators' Adoption of Pinning Inappropriate Comments as a Moderation Strategy." pith.science (2026). https://pith.science/paper/JQ7L2GV7

@misc{pith2026250514844,
  author       = {Pith},
  title        = {Pith review of: The Pin of Shame: Examining Content Creators' Adoption of Pinning Inappropriate Comments as a Moderation Strategy},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JQ7L2GV7}},
  note         = {Machine review of arXiv:2505.14844}
}
read the original abstract

Many social media platforms allow content creators to pin user comments in response to their content. Once pinned, a comment remains fixed at the top of the comments section, regardless of subsequent activity or the selected sorting order. The "Pin of Shame" refers to an innovative re-purposing of this feature, where creators intentionally pin norm-violating comments to spotlight them and prompt shaming responses from their audiences. This study explores how creators adopt this emerging moderation tactic, examining their motivations, its outcomes, and how it compares-procedurally and in effect-to other content moderation strategies. Through interviews with 20 content creators who had pinned negative comments on their posts, we find that the Pin of Shame is used to punish and educate inappropriate commenters, elicit emotional accountability, provoke audience negotiation of community norms, and support creators' impression management goals. Our findings shed light on the benefits, precarities, and risks of using public shaming as a tool for norm enforcement. We contribute to HCI research by informing the design of user-centered tools for addressing content-based harm.

Figures

Figures reproduced from arXiv: 2505.14844 by the authors.

Figure 1
Figure 1. Examples of Pin of Shame found on Instagram. Content creators pin the negative comments to fix [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Reply, Delete, or Ignore? Examining How Content Creators Perceive and Select Comment Moderation Strategies

    cs.HC 2026-08 conditional novelty 5.0 of 10

    Content creators' moderation choices (delete, reply, ignore) are driven by perceived safety and public image benefits, but not by expected algorithmic rewards; deletion is seen as safest, replying as most algorithmica...

Reference graph

Works this paper leans on

117 extracted references · 60 canonical work pages · cited by 1 Pith paper

  1. [1]

    Anti-Defamation League. 2024. Online Hate and Harassment: The American Experience. https://www.adl.org/ sites/default/files/documents/2024-06/online-hate-and-harassment-the-american-experience-v2024.pdf Accessed: 2025-02-03

    2024

  2. [2]

    Mariam Asad. 2019. Prefigurative design as a method for research justice.Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1–18

    2019

  3. [3]

    Rajesh Basak, Niloy Ganguly, Shamik Sural, and Soumya K Ghosh. 2016. Look before you shame: A study on shaming activities on Twitter. In Proceedings of the 25th international conference companion on world wide web . 11–12

    2016

  4. [4]

    Rajesh Basak, Shamik Sural, Niloy Ganguly, and Soumya K Ghosh. 2019. Online public shaming on Twitter: Detection, analysis, and mitigation. IEEE Transactions on computational social systems 6, 2 (2019), 208–220

    2019

  5. [5]

    Rachel Berryman and Misha Kavka. 2017. ‘I Guess A Lot of People See Me as a Big Sister or a Friend’: the role of intimacy in the celebrification of beauty vloggers. Journal of Gender Studies 26, 3 (2017), 307–320. https: //doi.org/10.1080/09589236.2017.1288611 arXiv:https://doi.org/10.1080/09589236.2017.1288611

    work page arXiv 2017

  6. [6]

    Paul Billingham and Tom Parr. 2020. Enforcing social norms: The morality of public shaming. European Journal of Philosophy 28, 4 (2020), 997–1016

    2020

  7. [7]

    Lindsay Blackwell, Tianying Chen, Sarita Schoenebeck, and Cliff Lampe. 2018. When online harassment is perceived as justified. In Proceedings of the International AAAI Conference on Web and Social Media , Vol. 12

    2018

  8. [8]

    Catherine Blaya. 2019. Cyberhate: A review and content analysis of intervention strategies. Aggression and violent behavior 45 (2019), 163–172

    2019

Show all 117 references
  1. [9]

    Lillian Boxman-Shabtai. 2019. The practice of parodying: YouTube as a hybrid field of cultural production. Media, Culture & Society 41, 1 (2019), 3–20

    2019

  2. [10]

    John Braithwaite. 1989. Crime, shame and reintegration . Cambridge university press

    1989

  3. [11]

    Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77–101

    2006

  4. [12]

    Jens Brunk, Jana Mattern, and Dennis M Riehle. 2019. Effect of transparency and trust on acceptance of automatic online comment moderation systems. In 2019 IEEE 21st Conference on Business Informatics (CBI) , Vol. 1. IEEE, 429–435. J. ACM, Vol. 37, No. 4, Article 111. Publicat...

    2019

  5. [13]

    Jean Burgess and Joshua Green. 2018. YouTube: Online video and participatory culture . John Wiley & Sons

    2018

  6. [14]

    Jie Cai, Aashka Patel, Azadeh Naderi, and Donghee Yvette Wohn. 2024. Content Moderation Justice and Fairness on Social Media: Comparisons Across Different Contexts and Platforms. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems . 1–9

    2024

  7. [15]

    Steve Campbell, Melanie Greenwood, Sarah Prior, Toniele Shearer, Kerrie Walkem, Sarah Young, Danielle Bywaters, and Kim Walker. 2020. Purposive sampling: complex or simple? Research case examples.Journal of Research in Nursing 25, 8 (2020), 652–661. https://doi.org/10.1177/174...

    2020 doi

  8. [16]

    Zoey Chen and Jonah Berger. 2013. When, why, and how controversy causes conversation. Journal of Consumer Research 40, 3 (2013), 580–593

    2013

  9. [17]

    Conor Clune and Emma McDaid. 2024. Content moderation on social media: constructing accountability in the digital space. Accounting, Auditing & Accountability Journal 37, 1 (2024), 257–279

    2024

  10. [18]

    Frances Corry. 2021. Screenshot, save, share, shame: Making sense of new media through screenshots and public shame. First Monday (2021)

    2021

  11. [19]

    Kelley Cotter. 2019. Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram. New media & society 21, 4 (2019), 895–913

    2019

  12. [20]

    Kate Crawford and Tarleton Gillespie. 2016. What is a flag for? Social media reporting tools and the vocabulary of complaint. New Media & Society 18, 3 (2016), 410–428

    2016

  13. [21]

    Stuart Cunningham and David Craig. 2017. Being ‘really real’on YouTube: authenticity, community and brand culture in social media entertainment. Media International Australia 164, 1 (2017), 71–81

    2017

  14. [22]

    Amy De Vries. 2015. The use of social media for shaming strangers: Young people’s views. In 2015 48th Hawaii International Conference on System Sciences . IEEE, 2053–2062

    2015

  15. [23]

    What are you doing, TikTok?

    Daniel Delmonaco, Samuel Mayworm, Hibby Thach, Josh Guberman, Aurelia Augusta, and Oliver L Haimson. 2024. " What are you doing, TikTok?": How Marginalized Social Media Users Perceive, Theorize, and" Prove" Shadowbanning. Proceedings of the ACM on Human-Computer Interaction 8,...

    2024

  16. [24]

    Michael Ann DeVito. 2022. How transfeminine TikTok creators navigate the algorithmic trap of visibility via folk theorization. Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (2022), 1–31

    2022

  17. [25]

    Zeynep Direk. 2020. Politics of shame in Turkey: public shaming and mourning. Sophia 59, 1 (2020), 39–56

    2020

  18. [26]

    Bryan Dosono and Bryan Semaan. 2019. Moderation practices as emotional labor in sustaining online communities: The case of AAPI identity work on Reddit. In Proceedings of the 2019 CHI conference on human factors in computing systems. 1–13

    2019

  19. [27]

    Megan French and Jeff Hancock. 2017. What’s the folk theory? Reasoning about cyber-social systems. Reasoning About Cyber-Social Systems (February 2, 2017) (2017)

    2017

  20. [28]

    Ryan J Gallagher, Andrew J Reagan, Christopher M Danforth, and Peter Sheridan Dodds. 2018. Divergent discourse between protests and counter-protests:# BlackLivesMatter and# AllLivesMatter. PloS one 13, 4 (2018), e0195644

    2018

  21. [29]

    R Stuart Geiger. 2016. Bot-based collective blocklists in Twitter: the counterpublic moderation of harassment in a networked public space. Information, Communication & Society 19, 6 (2016), 787–803

    2016

  22. [30]

    Susan A Gelman and Cristine H Legare. 2011. Concepts and folk theories. Annual review of anthropology 40, 1 (2011), 379–398

    2011

  23. [31]

    Tarleton Gillespie. 2018. Custodians of the Internet: Platforms, content moderation, and the hidden decisions that shape social media. Yale University Press

    2018

  24. [32]

    Erving Goffman. 2023. The presentation of self in everyday life. In Social theory re-wired. Routledge, 450–459

    2023

  25. [33]

    João Gonçalves, Ina Weber, Gina M Masullo, Marisa Torres da Silva, and Joep Hofhuis. 2023. Common sense or censorship: How algorithmic moderators and message type influence perceptions of online content deletion. new media & society 25, 10 (2023), 2595–2617

    2023

  26. [34]

    Oliver L Haimson, Daniel Delmonaco, Peipei Nie, and Andrea Wegner. 2021. Disproportionate removals and differing content moderation experiences for conservative, transgender, and black social media users: Marginalization and moderation gray areas. Proceedings of the ACM on Hum...

    2021

  27. [35]

    Hamilton, Oliver Garretson, and Andruid Kerne

    William A. Hamilton, Oliver Garretson, and Andruid Kerne. 2014. Streaming on Twitch: Fostering Participatory Communities of Play within Live Mixed Media. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (Toronto, Ontario, Canada) (CHI ’14). Associat...

    2014

  28. [36]

    Yulin Hao and Xiaojie Li. 2024. Shaping the Influencers: The Role of Multi-Channel Networks. A vailable at SSRN 4720070 (2024)

    2024

  29. [37]

    Honestly, I Think TikTok has a Vendetta Against Black Creators

    Camille Harris, Amber Gayle Johnson, Sadie Palmer, Diyi Yang, and Amy Bruckman. 2023. "Honestly, I Think TikTok has a Vendetta Against Black Creators": Understanding Black Content Creator Experiences on TikTok. Proc. ACM Hum.-Comput. Interact. 7, CSCW2, Article 320 (Oct. 2023)...

    2023 doi

  30. [38]

    Zorah Hilvert-Bruce, James T Neill, Max Sjöblom, and Juho Hamari. 2018. Social motivations of live-streaming viewer engagement on Twitch. Computers in Human Behavior 84 (2018), 58–67

    2018

  31. [39]

    Yubo Hou, Tonglin Jiang, and Qi Wang. 2017. Socioeconomic status and online shaming: The mediating role of belief in a just world. Computers in Human Behavior 76 (2017), 19–25

    2017

  32. [40]

    Jane Im, Sonali Tandon, Eshwar Chandrasekharan, Taylor Denby, and Eric Gilbert. 2020. Synthesized social signals: Computationally-derived social signals from account histories. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems . 1–12

    2020

  33. [41]

    Did you suspect the post would be removed?

    Shagun Jhaver, Darren Scott Appling, Eric Gilbert, and Amy Bruckman. 2019. "Did you suspect the post would be removed?" Understanding user reactions to content removals on Reddit. Proceedings of the ACM on human-computer interaction 3, CSCW (2019), 1–33

    2019

  34. [42]

    Shagun Jhaver, Iris Birman, Eric Gilbert, and Amy Bruckman. 2019. Human-Machine Collaboration for Content Regulation: The Case of Reddit Automoderator. ACM Trans. Comput.-Hum. Interact. 26, 5, Article 31 (July 2019), 35 pages. https://doi.org/10.1145/3338243

    2019 doi

  35. [43]

    Shagun Jhaver, Amy Bruckman, and Eric Gilbert. 2019. Does transparency in moderation really matter? User behavior after content removal explanations on reddit. Proceedings of the ACM on Human-Computer Interaction 3, CSCW (2019), 1–27

    2019

  36. [44]

    Shagun Jhaver, Larry Chan, and Amy Bruckman. 2017. The view from the other side: The border between controversial speech and harassment on Kotaku in Action. arXiv preprint arXiv:1712.05851 (2017)

    2017 arXiv

  37. [45]

    Shagun Jhaver, Quan Ze Chen, Detlef Knauss, and Amy X Zhang. 2022. Designing word filter tools for creator-led comment moderation. In Proceedings of the 2022 CHI conference on human factors in computing systems . 1–21

    2022

  38. [46]

    Shagun Jhaver, Seth Frey, and Amy X. Zhang. 2023. Decentralizing Platform Power: A Design Space of Multi-level Governance in Online Social Platforms. Social Media + Society (2023), 10 pages

    2023

  39. [47]

    Shagun Jhaver, Sucheta Ghoshal, Amy Bruckman, and Eric Gilbert. 2018. Online harassment and content moderation: The case of blocklists. ACM Transactions on Computer-Human Interaction (TOCHI) 25, 2 (2018), 1–33

    2018

  40. [48]

    Shagun Jhaver, Himanshu Rathi, and Koustuv Saha. 2024. Bystanders of Online Moderation: Examining the Effects of Witnessing Post-Removal Explanations. In Proceedings of the CHI Conference on Human Factors in Computing Systems . 1–9

    2024

  41. [49]

    Shagun Jhaver, Alice Qian Zhang, Quan Ze Chen, Nikhila Natarajan, Ruotong Wang, and Amy X Zhang. 2023. Personalizing content moderation on social media: User perspectives on moderation choices, interface design, and labor. Proceedings of the ACM on Human-Computer Interaction 7...

    2023

  42. [50]

    Jialun Aaron Jiang, Peipei Nie, Jed R Brubaker, and Casey Fiesler. 2023. A trade-off-centered framework of content moderation. ACM Transactions on Computer-Human Interaction 30, 1 (2023), 1–34

    2023

  43. [51]

    Jialun Aaron Jiang, Morgan Klaus Scheuerman, Casey Fiesler, and Jed R Brubaker. 2021. Understanding international perceptions of the severity of harmful content online. PloS one 16, 8 (2021), e0256762

    2021

  44. [52]

    Grace Maria Jochan and Trina Banerjee. 2021. Shaming in the Internet Era: Evaluating the reintegrative function of shame in digital spaces. Shame 4.0: Investigating an Emotion in Digital Worlds and the Fourth Industrial Revolution (2021), 431–454

    2021

  45. [53]

    Nicholas John. 2024. A Classification of Features for Interpersonal Disconnectivity in Digital Media: Block, Unfriend, Unfollow, Mute, Withhold, and Eject. Media and Communication 12, Article 8716 (2024)

    2024

  46. [54]

    Prerna Juneja, Deepika Rama Subramanian, and Tanushree Mitra. 2020. Through the Looking Glass: Study of Transparency in Reddit’s Moderation Practices. Proceedings of the ACM on Human-Computer Interaction 4, GROUP (2020), 1–35

    2020

  47. [55]

    Nadia Karizat, Dan Delmonaco, Motahhare Eslami, and Nazanin Andalibi. 2021. Algorithmic folk theories and identity: How TikTok users co-produce knowledge of identity and engage in algorithmic resistance. Proceedings of the ACM on human-computer interaction 5, CSCW2 (2021), 1–44

    2021

  48. [56]

    Anita Kasabova. 2021. Shame Dwells in the Eyes: Analysing Social Media Culture Using Aristotle’s Perspectives. Shame 4.0: Investigating an Emotion in Digital Worlds and the Fourth Industrial Revolution (2021), 371–388

    2021

  49. [57]

    Haesoo Kim, HaeEun Kim, Juho Kim, and Jeong-woo Jang. 2022. When does it become harassment? An investigation of online criticism and calling out in twitter. Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (2022), 1–32

    2022

  50. [58]

    del Pobil

    Jina Kim, Kunwoo Bae, Eunil Park, and Angel P. del Pobil. 2019. Who Will Subscribe to My Streaming Channel? The Case of Twitch. In Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing (Austin, TX, USA) (CSCW ’19). Association...

    2019

  51. [59]

    Nancy S. Kim. 2009. Website Proprietorship and Online Harassment. https://papers.ssrn.com/sol3/papers.cfm? abstract{_}id=1354466 J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2025. 111:20 Shim and Jhaver

    2009

  52. [60]

    Kate Klonick. 2015. Re-shaming the debate: Social norms, shame, and regulation in an internet age. Md. L. Rev. 75 (2015), 1029

    2015

  53. [61]

    Dialing it Back:

    Sena A. Kojah, Ben Zefeng Zhang, Carolina Are, Daniel Delmonaco, and Oliver L. Haimson. 2025. "Dialing it Back:" Shadowbanning, Invisible Digital Labor, and how Marginalized Content Creators Attempt to Mitigate the Impacts of Opaque Platform Governance. Proc. ACM Hum.-Comput. ...

    2025 doi

  54. [62]

    Yubo Kou. 2021. Punishment and its discontents: An analysis of permanent ban in an online game community. Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (2021), 1–21

    2021

  55. [63]

    Yubo Kou and Xinning Gui. 2021. Flag and flaggability in automated moderation: The case of reporting toxic behavior in an online game community. In Proceedings of the 2021 CHI conference on human factors in computing systems . 1–12

    2021

  56. [64]

    Patricia G Lange. 2007. Commenting on comments: Investigating responses to antagonism on YouTube. In Society for Applied anthropology conference, Vol. 31. 163–190

    2007

  57. [65]

    Thomer, and Cliff Lampe

    Song Mi Lee, Andrea K. Thomer, and Cliff Lampe. 2022. The Use of Negative Interface Cues to Change Perceptions of Online Retributive Harassment. Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 334 (Nov. 2022), 23 pages. https://doi.org/10.1145/3555226

    2022 doi

  58. [66]

    We dissect stupidity and respond to it

    Rebecca Lewis, Alice E Marwick, and William Clyde Partin. 2021. “We dissect stupidity and respond to it”: Response videos and networked harassment on YouTube. American Behavioral Scientist 65, 5 (2021), 735–756

    2021

  59. [67]

    Hanlin Li, Brent Hecht, and Stevie Chancellor. 2022. All that’s happening behind the scenes: Putting the spotlight on volunteer moderator labor in reddit. In Proceedings of the International AAAI Conference on Web and Social Media , Vol. 16. 584–595

    2022

  60. [68]

    Hanlin Li, Brent Hecht, and Stevie Chancellor. 2022. Measuring the monetary value of online volunteer work. In Proceedings of the International AAAI Conference on Web and Social Media , Vol. 16. 596–606

    2022

  61. [69]

    Jie Li, Xinning Gui, Yubo Kou, and Yukun Li. 2019. Live Streaming as Co-Performance: Dynamics between Center and Periphery in Theatrical Engagement. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 64 (nov 2019), 22 pages. https://doi.org/10.1145/3359166

    2019 doi

  62. [70]

    Hugo Liu. 2007. Social network profiles as taste performances. Journal of computer-mediated communication 13, 1 (2007), 252–275

    2007

  63. [71]

    I Upload... All Types of Different Things to Say the World of Blindness Is More Than What They Think It Is

    Yao Lyu, Jie Cai, Bryan Dosono, Davis Yadav, and John M Carroll. 2024. " I Upload... All Types of Different Things to Say the World of Blindness Is More Than What They Think It Is": A Study of Blind TikTokers’ Identity Work from a Flourishing Perspective. Proceedings of the AC...

    2024

  64. [72]

    How advertiser-friendly is my video?

    Renkai Ma and Yubo Kou. 2021. "How advertiser-friendly is my video?": YouTuber’s Socioeconomic Interactions with Algorithmic Content Moderation. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 429 (Oct. 2021), 25 pages. https://doi.org/10.1145/3479573

    2021 doi

  65. [73]

    Defaulting to boilerplate answers, they didn’t engage in a genuine conversation

    Renkai Ma and Yubo Kou. 2023. "Defaulting to boilerplate answers, they didn’t engage in a genuine conversation": Dimensions of Transparency Design in Creator Moderation. Proc. ACM Hum.-Comput. Interact. 7, CSCW1, Article 44 (April 2023), 26 pages. https://doi.org/10.1145/3579477

    2023 doi

  66. [74]

    Renkai Ma, Yue You, Xinning Gui, and Yubo Kou. 2023. How Do Users Experience Moderation?: A Systematic Literature Review. Proc. ACM Hum.-Comput. Interact.7, CSCW2, Article 278 (Oct. 2023), 30 pages. https://doi.org/10.1145/3610069

    2023 doi

  67. [75]

    Zhang, and David Karger

    Kaitlin Mahar, Amy X. Zhang, and David Karger. 2018. Squadbox: A Tool to Combat Email Harassment Using Friendsourced Moderation. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI ’18). Association for Computing Machinery...

    2018

  68. [76]

    Carmel Maher, Mark Hadfield, Maggie Hutchings, and Adam De Eyto. 2018. Ensuring rigor in qualitative data analysis: A design research approach to coding combining NVivo with traditional material methods. International journal of qualitative methods 17, 1 (2018), 1609406918786362

    2018

  69. [77]

    I like them, but won’t ‘like’them

    Ben Marder, Emma Slade, David Houghton, and Chris Archer-Brown. 2016. “I like them, but won’t ‘like’them”: An examination of impression management associated with visible political party affiliation on Facebook. Computers in Human Behavior 61 (2016), 280–287

    2016

  70. [78]

    Alice E Marwick. 2015. You may know me from youtube:(micro-) celebrity in social media. A companion to celebrity (2015), 333–350

    2015

  71. [79]

    Alice E Marwick. 2021. Morally motivated networked harassment as normative reinforcement. Social Media+ Society 7, 2 (2021), 20563051211021378

    2021

  72. [80]

    Alice E Marwick and Danah Boyd. 2011. I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience. New media & society 13, 1 (2011), 114–133

    2011

  73. [81]

    Alice E Marwick and Robyn Caplan. 2018. Drinking male tears: Language, the manosphere, and networked harassment. Feminist media studies 18, 4 (2018), 543–559. J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2025. Pinning Inappropriate Comments as a Moderation Str...

    2018

  74. [82]

    Gina Masullo Chen, Paromita Pain, and Jinglun Zhang. 2018. # NastyWomen: Reclaiming the Twitterverse from misogyny. Mediating misogyny: Gender, technology, and harassment (2018), 371–388

    2018

  75. [83]

    J Nathan Matias. 2019. Preventing harassment and increasing group participation through social norms in 2,190 online science discussions. Proceedings of the National Academy of Sciences 116, 20 (2019), 9785–9789

    2019

  76. [84]

    Shannon R Muir, Lynne D Roberts, and Lorraine P Sheridan. 2021. The portrayal of online shaming in contemporary online news media: A media framing analysis. Computers in human behavior reports 3 (2021), 100051

    2021

  77. [85]

    Maria Murumaa-Mengel and Liisi Maria Muuli. 2021. Misogynist content exposé pages on Instagram: Five types of shamings, moderators and audience members. Participations: Journal of Audience and Reception Studies 18, 2 (2021), 100–123

    2021

  78. [86]

    Sarah Myers West. 2018. Censored, suspended, shadowbanned: User interpretations of content moderation on social media platforms. New Media & Society 20, 11 (2018), 4366–4383

    2018

  79. [87]

    Martha C Nussbaum. 2019. Shaming Citizens? In Shame Punishment. Routledge, 275–338

    2019

  80. [88]

    Marie Ozanne, Aparajita Bhandari, Natalya N Bazarova, and Dominic DiFranzo. 2022. Shall AI moderators be made visible? Perception of accountability and trust in moderation systems on social media platforms. Big Data & Society 9, 2 (2022), 20539517221115666

    2022

  81. [89]

    Anthony J Pellicone and June Ahn. 2017. The Game of Performing Play: Understanding streaming as cultural production. In Proceedings of the 2017 CHI conference on human factors in computing systems . 4863–4874

    2017

  82. [90]

    Pew Research Center. 2021. The State of Online Harassment . Pew Research Center. https://www.pewresearch.org/ internet/2021/01/13/the-state-of-online-harassment/

    2021

  83. [91]

    Tobias Raun. 2018. Capitalizing intimacy: New subcultural forms of micro-celebrity strategies and affective labour on YouTube. Convergence 24, 1 (2018), 99–113

    2018

  84. [92]

    Yim Register, Izzi Grasso, Lauren N Weingarten, Lilith Fury, Constanza Eliana Chinea, Tuck J Malloy, and Emma S Spiro. 2024. Beyond Initial Removal: Lasting Impacts of Discriminatory Content Moderation to Marginalized Creators on Instagram. Proceedings of the ACM on Human-Comp...

    2024

  85. [93]

    Sarah T Roberts. 2019. Behind the Screen: Content Moderation in the Shadows of Social Media . Yale University Press

    2019

  86. [94]

    Jon Ronson. 2015. So you’ve been publicly shamed . Picador

    2015

  87. [95]

    Minna Ruckenstein and Linda Lisa Maria Turunen. 2020. Re-humanizing the platform: Content moderators and the logic of care. New media & society 22, 6 (2020), 1026–1042

    2020

  88. [96]

    Niloufar Salehi, Roya Pakzad, Nazita Lajevardi, and Mariam Asad. 2023. Sustained harm over time and space limits the external function of online counterpublics for American Muslims. Proceedings of the ACM on Human-Computer Interaction 7, CSCW1 (2023), 1–24

    2023

  89. [97]

    Thomas Scheff. 2014. The ubiquity of hidden shame in modernity. Cultural Sociology 8, 2 (2014), 129–141

    2014

  90. [98]

    Branham, and Foad Hamidi

    Morgan Klaus Scheuerman, Stacy M. Branham, and Foad Hamidi. 2018. Safe Spaces and Safe Places: Unpacking Technology-Mediated Experiences of Safety and Harm with Transgender People. Proc. ACM Hum.-Comput. Interact. 2, CSCW (Nov. 2018), 155:1–155:27. https://doi.org/10.1145/3274424

    2018 doi

  91. [99]

    Brubaker

    Morgan Klaus Scheuerman, Jialun Aaron Jiang, Casey Fiesler, and Jed R. Brubaker. 2021. A Framework of Severity for Harmful Content Online. Proc. ACM Hum.-Comput. Interact. 5, CSCW2 (Oct. 2021), 368:1–368:33. https://doi.org/10. 1145/3479512

    2021

  92. [100]

    Sarita Schoenebeck, Oliver L Haimson, and Lisa Nakamura. 2021. Drawing from justice theories to support targets of online harassment. new media & society 23, 5 (2021), 1278–1300

    2021

  93. [101]

    Ashley L Shea, Aspen KB Omapang, Ji Yong Cho, Miryam Y Ginsparg, Natalie Bazarova, Winice Hui, René F Kizilcec, Chau Tong, and Drew Margolin. 2024. Discursive objection strategies in online comments: Developing a classification schema and validating its training. arXiv preprin...

    2024 arXiv

  94. [102]

    Yunhee Shim and Shagun Jhaver. 2024. Incorporating Procedural Fairness in Flag Submissions on Social Media Platforms. arXiv preprint arXiv:2409.08498 (2024)

    2024 arXiv

  95. [103]

    Mohit Singhal, Chen Ling, Pujan Paudel, Poojitha Thota, Nihal Kumarswamy, Gianluca Stringhini, and Shirin Nilizadeh

  96. [104]

    Riedl, and Matthew Lease

    Miriah Steiger, Timir J Bharucha, Sukrit Venkatagiri, Martin J. Riedl, and Matthew Lease. 2021. The Psychological Well-Being of Content Moderators: The Emotional Labor of Commercial Moderation and Avenues for Improving Support. In Proceedings of the 2021 CHI Conference on Huma...

    2021

  97. [105]

    Jan E Stets and Peter J Burke. 2000. Identity theory and social identity theory. Social psychology quarterly (2000), 224–237

    2000

  98. [106]

    Nicolas P Suzor, Sarah Myers West, Andrew Quodling, and Jillian York. 2019. What do we mean when we talk about transparency? Toward meaningful transparency in commercial content moderation. International Journal of J. ACM, Vol. 37, No. 4, Article 111. Publication date: August ...

    2019

  99. [107]

    JP Tangney. 1995. Shame and guilt in interpersonal relationships. Self-conscious emotions: The psychology shame, guilt, embarrassment and pride/Guilford (1995)

    1995

  100. [108]

    It’s common and a part of being a content creator

    Kurt Thomas, Patrick Gage Kelley, Sunny Consolvo, Patrawat Samermit, and Elie Bursztein. 2022. “It’s common and a part of being a content creator”: Understanding How Creators Experience and Cope with Hate and Harassment Online. In Proceedings of the 2022 CHI conference on huma...

    2022

  101. [109]

    Daniel Trottier. 2018. Coming to terms with shame: Exploring mediated visibility against transgressions. Surveillance and Society 16, 2 (2018), 170–182

    2018

  102. [110]

    At the End of the Day Facebook Does What ItWants

    Kristen Vaccaro, Christian Sandvig, and Karrie Karahalios. 2020. " At the End of the Day Facebook Does What ItWants" How Users Experience Contesting Algorithmic Content Moderation. Proceedings of the ACM on human-computer interaction 4, CSCW2 (2020), 1–22

    2020

  103. [111]

    Jessica Vitak, Kalyani Chadha, Linda Steiner, and Zahra Ashktorab. 2017. Identifying women’s experiences with and strategies for mitigating negative effects of online harassment. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Comput...

    2017

  104. [112]

    Emily A Vogels. 2021. The state of online harassment . Vol. 13. Pew Research Center Washington, DC

    2021

  105. [113]

    Donghee Yvette Wohn. 2019. Volunteer moderators in twitch micro communities: How they get involved, the roles they play, and the emotional labor they experience. In Proceedings of the 2019 CHI conference on human factors in computing systems. 1–13

    2019

  106. [114]

    Donghee Yvette Wohn and Guo Freeman. 2020. Audience Management Practices of Live Streamers on Twitch. In ACM International Conference on Interactive Media Experiences (Cornella, Barcelona, Spain) (IMX ’20). Association for Computing Machinery, New York, NY, USA, 106–116. https...

    2020

  107. [115]

    Sijia Xiao, Shagun Jhaver, and Niloufar Salehi. 2023. Addressing interpersonal harm in online gaming communities: The opportunities and challenges for a restorative justice approach.ACM Transactions on Computer-Human Interaction 30, 6 (2023), 1–36

    2023

  108. [116]

    Alice Qian Zhang, Kaitlin Montague, and Shagun Jhaver. 2023. Cleaning up the streets: Understanding motivations, mental models, and concerns of users flagging social media posts. arXiv preprint arXiv:2309.06688 (2023). J. ACM, Vol. 37, No. 4, Article 111. Publication date: August 2025

    2023 arXiv

  109. [2023]

    In 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P)

    SoK: Content moderation in social media, from guidelines to enforcement, and research to practice. In 2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P) . IEEE, 868–895

    2023

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.