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REVIEW 3 major objections 6 minor 99 references

Understanding Community-Level Blocklists in Decentralized Social Media

T0 review · 3 major / 6 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read This paper studies community-level blocklists on Mastodon, showing that most instances keep them private and that moderators balance openness, safety, and context when blocking entire communities, and it argues for redesigning blocklist…

desk verdict The most complete map yet of Mastodon blocklists, with a real but fixable measurement caveat in the headline transparency statistic. read the letter →

arxiv 2506.05522 v1 pith:IWQWUG5H submitted 2025-06-05 cs.SI cs.HC

Owen Xingjian Zhang , Sohyeon Hwang , Yuhan Liu , Manoel Horta Ribeiro , Andrés Monroy-Hernández This is my paper
classification cs.SIcs.HC
keywords contentmoderationblocklistsMastodonFediversedecentralizedsocialmediatoolscommunitygovernancequalitativeinterviews
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 studies community-level blocklists on Mastodon, the lists by which one server blocks an entire other server from interacting with it. It claims that blocklists are the key cross-community moderation tool in decentralized social media, yet they are rarely shared and poorly understood. Combining a content analysis of 1,807 Mastodon instances, five shared blocklists, and four management tools with twelve moderator interviews, the authors find wide variation in blocklist goals, criteria, and transparency, and identify three moderation styles that balance openness, safety, and context. The result matters because if the paper is right, blocklist tooling should be redesigned around category filters, severity toggles, comment receipts, and collaborative decision-making rather than simple import-export lists.

What carries the argument

The central object is the community-level blocklist itself, defined as a list by which a Mastodon instance blocks another entire instance. The argument is carried by two analytic instruments: a coding scheme that characterizes blocklists and tools along dimensions of purpose, criteria, transparency, distribution, limitations, and additional content, and an interview-derived framework of three moderator decision styles (responsive/openness, proactive/safety, measured/context). A lightweight prototype interface with category filters, severity toggles, and comments served as a design probe to elicit user needs. Together these allow the paper to move from describing the ecosystem to proposing concrete design directions.

What would settle it

A census or large random sample of Mastodon instances that includes non-English and very small instances could settle the generalization question: if those instances show a substantially different public-sharing rate, or if interviews with their moderators do not reproduce the three decision styles and the same design needs, then the paper's framework and recommendations would not generalize.

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Extended reading notes

Core claim

The paper's central claim is that community-level blocklists in the Fediverse are not monolithic: among 1,807 instances with at least 10 active users, only 364 (20.1%) publicly share blocklists, and fewer than half of those give explicit reasons; the shared blocklists that do exist differ in whether they seek broad consensus or target severe actors, and in how much they disclose their sources. Interviews with twelve moderators show that blocklist use follows three decision styles — responsive and openness-prioritizing, proactive and safety-prioritizing, and measured and context-prioritizing — which moderators move between rather than choose once. On this basis the paper argues that current tools fail to support the collaborative, transparent, and flexible practices moderators want, and that features such as category filters, severity toggles, comment receipts, and collaborative voting would better match how moderation actually happens.

Load-bearing premise

The findings rest on the assumption that the twelve moderators and the five curated blocklists and four tools represent the broader Mastodon ecosystem, even though the selection skews toward English-language, publicly visible, widely referenced resources and instances with at least ten active users.

Editorial extensions

If this is right

  • Blocklist management tools should add category filters and severity toggles so moderators can see what an entry is about and choose an action level per instance.
  • Comment receipts and public annotations should become standard, since moderators already use private comments to keep decisions justifiable, renewable, and reviewable.
  • Design should support collaborative workflows, including voting, suspect lists, shared receipt libraries, and blocklist subscription and merging across instances.
  • Shared blocklists should be framed as starter resources with documented sources and biases, not as definitive lists, because they vary in consensus-based versus severity-based criteria.
  • Moderator support should accommodate movement among responsive, proactive, and manual-review styles rather than assuming one fixed workflow.

Reading between the lines

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

  • We infer that the reported 20.1% public-sharing rate likely overstates ecosystem transparency, because the sample excluded instances with fewer than 10 active users, and the paper's own size trend suggests the smallest instances share least.
  • We infer that the openness/safety/context triangle could generalize as an analytic lens to other federated or protocol-based platforms beyond Mastodon, though the paper only studies Mastodon and cautions against such generalization.
  • We infer that standardizing tags and category definitions across blocklists, with multilingual support, could be tested as a way to reduce false-positive blocking and cross-instance misunderstandings, building on the paper's finding that tools currently lack standardized categorization.
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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

3 major / 6 minor

Summary. The paper studies community-level blocklists in Mastodon, a decentralized social media platform. It combines a content analysis of the blocklist landscape (based on scraping 1,807 Mastodon instances with at least 10 active users, a curated selection of five shared blocklists, and four blocklist-related tools) with semi-structured interviews of 12 Mastodon moderators from seven countries. The central claims are that only 20.1% of instances publicly share blocklists; that shared blocklists vary in purpose, inclusion criteria, and transparency; that moderators balance three decision-making styles prioritizing openness, safety, and context; and that design improvements such as category filters, severity toggles, comment receipts, and collaborative voting would support moderation. The paper also presents a lightweight demo system used as a design probe during interviews, and derives implications for transparency and collaborative moderation in decentralized systems.

Significance. If the findings hold, the paper provides one of the first systematic, mixed-method characterizations of community-level blocklists in decentralized social media, filling a gap between individual-level blocklist research and platform-level moderation studies. The work has concrete strengths: a multi-method design; a multi-country interview sample with direct quotes; comparative tables of five blocklists and four tools; and a working prototype used as a design probe, which grounds the design recommendations in concrete participant reactions. The proposed design features and the three-part framework of moderation approaches are actionable for future research and tool development. The main quantitative anchor, however, is vulnerable to measurement-validity concerns described below, and the single-coder coding process limits confidence in the qualitative categories.

major comments (3)
  1. [§3.2.1 and §4.1.1] The claim that only 364 of 1,807 instances (20.1%) publicly share blocklists is operationalized by scraping only each instance's About page. However, the shared blocklists analyzed in §3.2.2 are explicitly distributed through external channels — public CSVs, Git/Codeberg repositories, and synchronization tools such as FediBlockHole and FediCheck — rather than through About pages alone. If any substantial number of the 1,807 instances publish, subscribe to, or link their blocklists through such channels without rendering them on the About page, the 20.1% figure undercounts actual public sharing. This statistic is load-bearing for the conclusion that 'explicit transparency in moderation remains limited' and for the design recommendations in §5.3.2. Please either broaden the measurement to include external blocklist channels (e.g., querying domain-block API endpoints, checking instance metadata, or searching public repositories) or reframe the claim as 'About-page-visible transparency,' and explicitly acknowledge this constraint in the limitations section, which currently only discusses selection skew of curated resources.
  2. [§3.2.2 and §3.3.4] The content analysis of blocklists and tools and the thematic analysis of interviews were both conducted by the first author alone, with no inter-rater reliability or second-coder agreement reported. The Tables 4 and 5 categories (Purpose, Criteria, Transparency, Distribution, etc.) and the three moderation styles reported in §4.2 are central to the paper's findings; a single-coder process without an agreement check leaves the reliability of these categorizations unestablished. Please report a second coder on a subset of the data with agreement metrics (e.g., Cohen's kappa), or explicitly justify and contextualize the single-coder approach with reference to established qualitative methods, and describe how the iterative author feedback changed the coding.
  3. [§3.2.1] The scraping pipeline is underspecified. The paper states only that 'automated scraping' with Octoparse was used to extract blocked domains and reasons from About pages, with no details on extraction rules, handling of dynamic or paginated content, validation or de-duplication of blocked domains, or how 'publicly share' was judged (e.g., whether any visible block section counts). This undermines reproducibility and makes it difficult for readers to assess potential measurement error in the headline 20.1% statistic. Please provide a detailed data-collection protocol, including the exact scrape date, URL patterns, inclusion/exclusion criteria, and ideally release the anonymized dataset or scripts so that the statistic can be independently checked.
minor comments (6)
  1. [Author list] The author list in the header contains 'SOHYEON HW ANG' with a spurious space; this should be corrected to 'Hwang'.
  2. [Footnote 11] Footnote 11 is truncated ('e.g., NSFW content would not work for a professionally-oriented instance') and appears to be an incomplete sentence; please complete or integrate it into the main text.
  3. [Table 3a] Table 3a reports percentages for each instance-size band but omits the denominators for the Yes and No columns; adding the totals would help readers verify the percentages and understand the unequal group sizes.
  4. [Appendix / reproducibility] The paper does not provide the interview protocol or the final codebook; including these in an appendix would strengthen transparency and allow other researchers to replicate or extend the thematic analysis.
  5. [References] A number of references have incomplete bibliographic details (e.g., [1], [33], [63] lack full venue or publication data); please bring all entries into consistent style for the target venue.
  6. [§8] The disclosure of LLM usage in Section 8 is explicit and appropriate, and the described scope of use is consistent with common editorial assistance.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the paper is an empirical interview and content-analysis study whose findings come from external data, not from equations or fitted parameters.

full rationale

The paper makes no formal derivation and contains no fitted parameters or predictive claims that could reduce to inputs by construction. The load-bearing findings come from two external empirical sources: scraped data from 1,807 Mastodon instances' public About pages (Sections 3.2.1 and 4.1.1) and semi-structured interviews with 12 moderators (Section 3.3). The content-analysis categories (Purpose, Criteria, Transparency, etc.) are analytic lenses defined before coding, not derived from the outcomes; reporting variation across blocklists is a description of the coded data, not a prediction of it. The three moderation decision styles (responsive, proactive, and measured) are induced from interview transcripts through standard thematic analysis, so they are not equivalent to the interview protocol by construction. Self-citations (Hwang et al. 2025, ref [44]; Liu et al. 2025, ref [63]) appear only as related-work context supporting background claims about federated norms and Mastodon adoption; neither is used to justify the paper's central empirical findings or to rule out alternatives. The paper's own Section 6 limitations acknowledge selection bias and generalizability concerns, and the skeptic's concern about About-page-only measurement of public sharing is a measurement-validity limitation rather than a circularity because it does not make the 20.1% figure equal to an input assumption. Accordingly, no circular steps are identified.

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

This is an empirical qualitative study, so there are no fitted parameters or new postulated entities. The axioms are the sampling and measurement assumptions on which the descriptive claims rest; the prototype is a design probe used to elicit feedback, not an invented entity.

assumptions (4)
  • domain assumption Self-reported moderator practices and preferences accurately reflect their actual moderation behavior.
    All RQ2 and RQ3 findings draw on what 12 moderators said in semi-structured interviews (Section 3.3); the study does not observe blocking behavior directly or cross-check statements against moderation logs.
  • domain assumption The five curated blocklists and four tools represent the salient community-level blocklist ecosystem.
    Selection prioritized public accessibility, documentation, and adoption (Sections 3.2.2 and 3.2.3); Section 6 acknowledges this overlooks less prominent and non-English resources.
  • domain assumption instances.social records with 10 or more active users form a valid frame for the Fediverse instance population.
    The content analysis uses this sampling frame (Section 3.2.1 and Table 3a); smaller and unlisted instances are excluded, and the 8,700-instance total comes from joinmastodon.org's server list.
  • domain assumption Publicly visible About page blocklists capture an instance's actual blocking practice.
    The scraping in Section 3.2.1 only sees publicly listed domains; instances that keep blocklists private (the large majority) are counted as non-sharers, which directly shapes the 20.1% sharing figure.

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Cite this review

Pith. "Pith review of Understanding Community-Level Blocklists in Decentralized Social Media." pith.science (2026). https://pith.science/paper/IWQWUG5H

@misc{pith2026250605522,
  author       = {Pith},
  title        = {Pith review of: Understanding Community-Level Blocklists in Decentralized Social Media},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/IWQWUG5H}},
  note         = {Machine review of arXiv:2506.05522}
}
read the original abstract

Community-level blocklists are key to content moderation practices in decentralized social media. These blocklists enable moderators to prevent other communities, such as those acting in bad faith, from interacting with their own -- and, if shared publicly, warn others about communities worth blocking. Prior work has examined blocklists in centralized social media, noting their potential for collective moderation outcomes, but has focused on blocklists as individual-level tools. To understand how moderators perceive and utilize community-level blocklists and what additional support they may need, we examine social media communities running Mastodon, an open-source microblogging software built on the ActivityPub protocol. We conducted (1) content analysis of the community-level blocklist ecosystem, and (2) semi-structured interviews with twelve Mastodon moderators. Our content analysis revealed wide variation in blocklist goals, inclusion criteria, and transparency. Interviews showed moderators balance proactive safety, reactive practices, and caution around false positives when using blocklists for moderation. They noted challenges and limitations in current blocklist use, suggesting design improvements like comment receipts, category filters, and collaborative voting. We discuss implications for decentralized content moderation, highlighting trade-offs between openness, safety, and nuance; the complexity of moderator roles; and opportunities for future design.

Figures

Figures reproduced from arXiv: 2506.05522 by the authors.

Figure 1
Figure 1. Screenshot of the demo system, showcasing category filters, severity toggles, and comments. [PITH_FULL_IMAGE:figures/full_fig_p008_1.png] view at source ↗
Figure 2
Figure 2. Conceptual diagram showing the triangular balance among moderation priorities: [PITH_FULL_IMAGE:figures/full_fig_p017_2.png] view at source ↗

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Pith tools

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