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Research Summary: When Does the Public Become Suspicious of Bots? Demand-Side Evidence from Botometer Query Logs

Original authors
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Original source
arXiv — Computers and Society
Summary & Analysis prepared by
Aziz Shuaib Ausi
Resource type
Research Summary / Knowledge Resource
Resource published on AZIZ OS
18 September 2026
Reading time
1 min
Publication type
Knowledge Resource
Availability
Open access
About this Summary & Analysis

AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.

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Analysis of Botometer query logs from 2020 to 2023 reveals insights into public suspicion of automated accounts, primarily on Twitter. Suspicion spikes during platform crises, notably around the 2022 Musk-Twitter dispute. Accounts attracting scrutiny are typically older, more prolific, have larger follower counts, and focus on promotional, political, or cryptocurrency content. These collectively suspected accounts tend to exhibit higher bot scores.

Why it matters

Understanding the triggers and characteristics of public suspicion towards automated accounts is critical for managing platform integrity, user trust, and reputation. This insight informs strategies for mitigating the impact of bot-related crises and developing more resilient online communication environments.

Key insights

  • Public suspicion of automated accounts (bots) is measurable through bot-checking service query logs.
  • Collective suspicion significantly increases during major platform-related crises, such as the 2022 Musk-Twitter bot dispute.
  • Accounts drawing public suspicion are characterized by being older, more prolific, having more followers, and frequently posting content related to promotion, politics, or cryptocurrency.
  • Accounts that generate collective suspicion tend to have objectively higher bot scores, as indicated by the Botometer service.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2609.20661

Citation

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Verification ID
ASA-EXE-2026-00738
Version
v1.0 · r0
Issued
18 September 2026
Resource prepared by
Aziz Shuaib Ausi
Resource status
Research Summary / Knowledge Resource
Underlying work
When Does the Public Become Suspicious of Bots? Demand-Side Evidence from Botometer Query Logs
Original authors
Attribution requires verification
Original source
arXiv — Computers and Society
Provenance status
Attribution requires verification
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Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.

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