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arxiv: 2509.21092 · v2 · pith:N5DU76FRnew · submitted 2025-09-25 · 💻 cs.SI

Influence of the majority group on individual judgments in online spontaneous conversations

Diletta Goglia , Davide Vega , Alessio Gandelli This is my paper

Pith reviewed 2026-05-21 22:26 UTC · model grok-4.3

classification 💻 cs.SI
keywords anti-conformitysocial influenceonline conversationsjudgment formationsocial mediadigital tracesBayesian regressionpersuasive language
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The pith

In anonymous online conversations individuals preserve the majority's positive or negative judgment orientation yet diverge from its specific stance while increasing persuasive language after exposure.

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

The paper investigates how majority views shape individual judgments during everyday dilemmas discussed on social media. It operationalizes judgments from digital traces, applies Bayesian regression to detect shifts before and after group exposure, and examines linguistic changes in the motivations people give for their positions. Results indicate anti-conformity rather than full conformity: people retain the overall positive or negative direction but take a different concrete stance, and their language becomes more persuasive once the majority is visible. This pattern matters because it suggests anonymous online settings produce social influence dynamics that differ from classic offline conformity experiments.

Core claim

In spontaneous anonymous online conversations, individuals exhibit anti-conformity by preserving the majority's positive or negative orientation of judgments but diverging from its stance, with an accompanying increase in persuasive language after the group's views are disclosed. These effects are identified through measurements of disagreement, Bayesian regression on judgment formation shifts, and linguistic analysis of motivations tied to each judgment.

What carries the argument

Bayesian regression applied to judgment shifts before versus after group exposure, paired with linguistic analysis of persuasive language in stated motivations.

If this is right

  • Online social influence produces divergence in specific stances while alignment on overall orientation remains.
  • Disclosure of majority views increases the use of persuasive language in individual justifications.
  • Anonymous online environments generate anti-conformity patterns distinct from those observed in face-to-face settings.
  • Judgment expression changes measurably once individuals encounter the group's position through digital traces.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Platform features that delay or obscure majority visibility might reduce the observed divergence in stance.
  • The same anti-conformity pattern could appear in other text-based discussion forums beyond the studied social media site.
  • Designers of online deliberation tools could exploit the increase in persuasive language to surface more diverse arguments.
  • Replicating the analysis on conversations with varying degrees of anonymity would test whether the effect depends on perceived anonymity.

Load-bearing premise

Digital traces from social media posts can reliably stand in for individual judgments and the conversations studied are genuinely spontaneous and anonymous.

What would settle it

A controlled study that removes digital-trace mediation and forces participants to state judgments in real time while varying whether they see the majority position would show no anti-conformity divergence if the paper's claim is false.

Figures

Figures reproduced from arXiv: 2509.21092 by Alessio Gandelli, Davide Vega, Diletta Goglia.

Figure 1
Figure 1. Figure 1: : Experimental design of the judgments distribution comparison for the KS [PITH_FULL_IMAGE:figures/full_fig_p013_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: : Disagreement evolution over time, averaged over all discussions and grouped [PITH_FULL_IMAGE:figures/full_fig_p014_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: : Comparison of the two distributions of individual judgments expressed in [PITH_FULL_IMAGE:figures/full_fig_p017_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: : Odd ratios of the ten social dimensions for each final verdict. Plots on the [PITH_FULL_IMAGE:figures/full_fig_p020_4.png] view at source ↗
read the original abstract

This study investigates how the majority group influences individual judgment formation and expression in anonymous, spontaneous online conversations. Drawing on theories of social conformity and anti-conformity, we analyze everyday dilemmas discussed on social media. First, using digital traces to operationalize judgments, we measure the conversations' disagreement and apply Bayesian regression to capture shifts of judgments formation before and after the group's exposure. Then we analyze changes in judgment expression with a linguistic analysis of the motivations associated with each judgment. Results show anti-conformity behaviors: individuals preserve the majority's positive or negative orientation of judgments but diverge from its stance, with persuasive language increasing post-disclosure. Our findings highlight how online environments reshape social influence compared to offline contexts.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript examines how the majority influences individual judgments in anonymous spontaneous online conversations on social media. Using digital traces to operationalize judgments, it applies Bayesian regression to detect shifts before and after majority exposure and conducts linguistic analysis of motivations. The key finding is anti-conformity: individuals retain the majority's positive or negative orientation but diverge from its stance, accompanied by increased use of persuasive language after disclosure.

Significance. If the results are confirmed, this work advances understanding of social influence in digital environments by demonstrating anti-conformity patterns that differ from offline contexts. The use of observational data from real conversations and statistical modeling provides a scalable approach to studying judgment formation, potentially informing both theory and platform design.

major comments (3)
  1. [Methods] Details on data selection, disagreement measurement, and controls for topic and user effects are missing or insufficient. This opacity raises questions about whether the central anti-conformity result is robust to alternative specifications, as noted in the soundness assessment.
  2. [Analysis of judgment expression] The interpretation of post content as reflecting internal judgments lacks supporting validation, such as comparison to self-reports. This is load-bearing because strategic performative posting could produce the observed divergence and language shifts without any change in private judgment.
  3. [Bayesian regression] The regression models for pre/post shifts should include explicit robustness checks for alternative codings of 'stance' versus 'orientation' to rule out artifacts in the anti-conformity claim.
minor comments (2)
  1. [Abstract] Clarify the distinction between 'orientation of judgments' and 'stance' early in the paper for better readability.
  2. [Linguistic analysis] Provide more details on the specific linguistic features or tools used for identifying persuasive language.

Simulated Author's Rebuttal

3 responses · 1 unresolved

We thank the referee for their constructive feedback on our manuscript. Their comments have prompted us to clarify several aspects of our methodology and analysis. Below, we provide point-by-point responses to the major comments and outline the revisions we intend to make in the next version of the paper.

read point-by-point responses

  1. Referee: [Methods] Details on data selection, disagreement measurement, and controls for topic and user effects are missing or insufficient. This opacity raises questions about whether the central anti-conformity result is robust to alternative specifications, as noted in the soundness assessment.

    Authors: We agree that additional details are necessary to ensure reproducibility and to address concerns about robustness. In the revised manuscript, we will expand the Methods section with a comprehensive description of the data selection criteria from the social media platform, the precise operationalization of disagreement using valence and stance measures, and the incorporation of hierarchical Bayesian models with random effects for topics and individual users. Furthermore, we will report results from alternative model specifications to demonstrate the stability of the anti-conformity finding. revision: yes

  2. Referee: [Analysis of judgment expression] The interpretation of post content as reflecting internal judgments lacks supporting validation, such as comparison to self-reports. This is load-bearing because strategic performative posting could produce the observed divergence and language shifts without any change in private judgment.

    Authors: This is a valid concern regarding the distinction between expressed and internal judgments. Our study relies on observational data from anonymous online conversations, where self-reports are not available. We will add an explicit discussion of this limitation in the revised manuscript, emphasizing that the patterns observed in linguistic features and divergence are consistent with anti-conformity in expression. We argue that in spontaneous, anonymous settings, performative aspects are minimized compared to identified contexts, but we acknowledge this as a boundary condition of the work. revision: partial

  3. Referee: [Bayesian regression] The regression models for pre/post shifts should include explicit robustness checks for alternative codings of 'stance' versus 'orientation' to rule out artifacts in the anti-conformity claim.

    Authors: We appreciate this suggestion for strengthening the analysis. We will incorporate additional robustness analyses in the revised version, testing alternative codings and categorizations of stance and orientation. These checks will be presented to confirm that the core anti-conformity result—matching valence but diverging in specific stance—is not an artifact of our primary coding scheme. revision: yes

standing simulated objections not resolved
  • We cannot provide direct comparisons to self-reports, as the study is based on publicly available digital trace data from spontaneous conversations without participant surveys or access to private judgments.

Circularity Check

0 steps flagged

No significant circularity: observational empirical analysis

full rationale

The paper is an observational study that operationalizes judgments from digital traces in social media conversations, applies Bayesian regression to measure pre/post shifts, and performs linguistic analysis of motivations. No derivation chain, first-principles predictions, fitted parameters renamed as predictions, or load-bearing self-citations appear in the provided text or abstract. The central claims about anti-conformity behaviors are presented as results of data analysis rather than reducing by construction to the inputs or prior author work. This is a standard empirical finding with independent content from the dataset.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard social psychology assumptions about conformity and the validity of digital traces as proxies for judgments; no new entities are introduced and free parameters appear limited to those in the Bayesian model.

axioms (2)
  • domain assumption Digital traces from social media posts can be used to operationalize individual judgments and motivations.
    Invoked when measuring disagreement and performing linguistic analysis of motivations.
  • domain assumption The conversations studied are spontaneous and anonymous as described.
    Underpins the comparison to offline contexts and the claim about online reshaping of influence.

pith-pipeline@v0.9.0 · 5642 in / 1313 out tokens · 30220 ms · 2026-05-21T22:26:46.517686+00:00 · methodology

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Reference graph

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