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arxiv: 2606.27111 · v1 · pith:SKK3HXIRnew · submitted 2026-06-25 · 💻 cs.HC · cs.SI

Behind the Mask: A Taxonomic Analysis of Activities in Online Social Networks

Debora F De Souza , Gabriela Beltrao , Berta Chulvi , Sergio Dantonio , Mehmet Gokay Ozerim , Javier Torregrosa , Adrian Giron , Angel Panizo
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Pablo Miralles Gonzalez Helena Liz Javier Huertas Tato Sonia Sousa Alejandro Martin Monika Maciuliene David Camacho
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Pith reviewed 2026-06-26 02:14 UTC · model grok-4.3

classification 💻 cs.HC cs.SI
keywords disinformationonline social networkstaxonomymalicious actorsanti-migration discoursehuman-computer interactionsocial media analysis
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The pith

A taxonomy distinguishes malicious actors in online social networks by their characteristics, activities, and strategies for spreading disinformation.

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

The paper develops a taxonomy for identifying and categorizing malicious actors who spread disinformation on online social networks. It draws on input from subject matter experts and academic literature to map out how these actors operate and contribute to deceptive content. The authors describe the design process and apply the taxonomy in a case study of anti-migration discourse on social media. If the taxonomy holds, it offers a structured method to examine actor behaviors and inform the design of network systems.

Core claim

The authors present a taxonomy informed by collaboration with subject matter experts and a review of the academic literature that classifies the characteristics, activities, and strategies of malicious actors on OSNs and examines their contribution to the spread of disinformation, as shown through its application to anti-migration discourse in social media channels.

What carries the argument

A taxonomy of malicious actor activities in online social networks, developed through expert consultation and literature review, that organizes characteristics and strategies to distinguish actors.

Load-bearing premise

The taxonomy accurately captures and distinguishes the characteristics, activities, and strategies of malicious actors on OSNs based on subject matter expert input and literature without specified validation against independent data.

What would settle it

Independent researchers applying the taxonomy to the same collection of OSN accounts and achieving low agreement on actor classifications would indicate the taxonomy does not reliably distinguish actors.

Figures

Figures reproduced from arXiv: 2606.27111 by Adrian Giron, Alejandro Martin, Angel Panizo, Berta Chulvi, David Camacho, Debora F De Souza, Gabriela Beltrao, Helena Liz, Javier Huertas Tato, Javier Torregrosa, Mehmet Gokay Ozerim, Monika Maciuliene, Pablo Miralles Gonzalez, Sergio Dantonio, Sonia Sousa.

Figure 1
Figure 1. Figure 1: Details of the study design illustrating how the phases of the study are connected [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Participants mapped out the types of malicious actors and how they influence other members of OSN [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: The general attribution provides a four-layer analysis for classification of malicious actors’ roles and characteristics [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: The approach classification allows differentiating the kind of manipulation done in the malicious content, encompassing [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Six different strategies were identified as possible dissemination tactics [PITH_FULL_IMAGE:figures/full_fig_p009_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Example of two messages and the visualization of their annotations [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
read the original abstract

The broadcast of disinformation in online social networks (OSN) is a growing concern examined across several disciplines, including human-computer interaction (HCI). The pervasive issue has been prompting novel approaches to identify the malicious actors behind the dissemination of deceptive and fabricated content. Analyzing the characteristics and activities of these actors, we designed a taxonomy informed by collaboration with subject matter experts (SMEs) and a review of the academic literature. Our study explores how to distinguish the characteristics, activities, and strategies of malicious actors on OSN and examines how they contribute to the spread of disinformation. We describe the design process and the application of the taxonomy in a case study analyzing anti-migration discourse in social media channels, and reflect on its potential to aid researchers and practitioners in the responsible design of network systems.

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

2 major / 1 minor

Summary. The paper claims to have designed a taxonomy for distinguishing the characteristics, activities, and strategies of malicious actors on online social networks (OSNs) involved in disinformation dissemination. The taxonomy is developed via collaboration with subject matter experts (SMEs) and a review of academic literature; the manuscript describes the design process and applies the taxonomy in a case study of anti-migration discourse on social media channels, reflecting on its utility for researchers and practitioners in responsible network system design.

Significance. If validated for reproducibility, the taxonomy would supply a structured framework for HCI analysis of OSN malicious actors, building on SME input and literature synthesis with a concrete case-study demonstration. The approach credits external expertise and applies the result to anti-migration discourse, but the absence of reliability or external validation metrics limits immediate significance for detection or mitigation work.

major comments (2)
  1. [Design Process] Design process (as described in the abstract and methods): the taxonomy is presented as distinguishing malicious actors' characteristics, activities, and strategies, yet no inter-rater reliability statistics, pilot-coding agreement measures, or external validation against independent datasets are supplied; this directly undermines the central claim that the categories are reproducible rather than reflective of the consulted SMEs' views.
  2. [Case Study] Case study application (anti-migration discourse): the single case study is offered as demonstration but does not address completeness or accuracy testing of the taxonomy, leaving the claim that it captures strategies load-bearing without supporting evidence such as agreement metrics or comparison to alternative taxonomies.
minor comments (1)
  1. The abstract could specify the number of SMEs consulted and the exact scope or search terms of the literature review to allow readers to assess the synthesis process.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thoughtful and constructive comments on our manuscript. We address each major comment point by point below, providing clarifications on our methodological choices while remaining faithful to the scope and claims of the work.

read point-by-point responses

  1. Referee: [Design Process] Design process (as described in the abstract and methods): the taxonomy is presented as distinguishing malicious actors' characteristics, activities, and strategies, yet no inter-rater reliability statistics, pilot-coding agreement measures, or external validation against independent datasets are supplied; this directly undermines the central claim that the categories are reproducible rather than reflective of the consulted SMEs' views.

    Authors: The taxonomy was developed as a synthesis of subject-matter expert input and a review of the academic literature, following an iterative design process rather than a quantitative coding study. No multiple independent raters applied categories to a shared dataset, so inter-rater reliability or pilot-coding agreement metrics are not applicable and would misrepresent the methodology. Reproducibility is instead supported by the transparent documentation of the expert collaboration and literature synthesis steps, which other researchers can follow or adapt. We did not claim statistical reproducibility or external dataset validation, as these were outside the stated scope of constructing an initial conceptual taxonomy. We will add a brief clarifying sentence in the methods section to distinguish this approach from empirical coding studies. revision: partial

  2. Referee: [Case Study] Case study application (anti-migration discourse): the single case study is offered as demonstration but does not address completeness or accuracy testing of the taxonomy, leaving the claim that it captures strategies load-bearing without supporting evidence such as agreement metrics or comparison to alternative taxonomies.

    Authors: The case study is explicitly framed as an illustrative application to demonstrate how the taxonomy can be used in practice on anti-migration discourse, not as a validation, completeness test, or comparative evaluation. The manuscript makes no claim that the taxonomy has been shown to capture all strategies with quantitative evidence. We agree that future work could usefully include agreement metrics or comparisons, but such extensions lie beyond the current paper's focus on taxonomy development and initial demonstration. We will revise the discussion to state the illustrative purpose more explicitly and note the lack of formal validation metrics as a limitation. revision: yes

Circularity Check

0 steps flagged

No circularity: taxonomy derived from external SME input and literature review

full rationale

The paper's central process is the construction of a taxonomy informed by collaboration with subject matter experts and a review of the academic literature, as stated in the abstract. No equations, fitted parameters, self-referential predictions, or load-bearing self-citations are present that would reduce any claim to its own inputs by construction. The derivation chain relies on external sources and is therefore self-contained with no reduction to internal definitions or prior author work.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The claim rests on the domain assumption that expert collaboration and literature review yield a useful taxonomy for distinguishing malicious actors, with no free parameters or invented entities introduced.

axioms (1)
  • domain assumption A taxonomy derived from subject matter experts and academic literature can effectively distinguish characteristics, activities, and strategies of malicious actors in OSNs
    Invoked in the abstract to justify the taxonomy design and its application to the case study.

pith-pipeline@v0.9.1-grok · 5720 in / 1220 out tokens · 23388 ms · 2026-06-26T02:14:58.105067+00:00 · methodology

discussion (0)

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Reference graph

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