Public suspicion of bots rises with Twitter controversies and account traits
When Does the Public Become Suspicious of Bots? Demand-Side Evidence from Botometer Query Logs
Computers and SocietySocial and Information Networks
Summary
People get suspicious about whether Twitter accounts are actually bots who post automatically. The authors looked at over a million checks made using a popular bot-detection tool called Botometer between 2020 and 2023. They found that suspicion spikes during big Twitter events like the 2022 dispute involving Elon Musk. Suspicious accounts tend to be older, have more followers, and post political, promotional, or crypto content. This shows that many people help catch bots by checking accounts, making the platform safer and more transparent.
What this means in practice
- •For social media platform moderators: Identify periods and account types that trigger increased public suspicion to improve bot monitoring policies.
- •For social media analytics teams: Use bot suspicion patterns tied to political and promotional content to enhance detection and reporting tools.
Authors
Tuğrulcan Elmas
Abstract
We study private bot-checking behavior from the demand side: when people suspect an account is automated, whom they suspect, and what follows. Using Botometer's server-side query logs, the most widely used bot-detection service, we treat each query as a behavioural trace of suspicion. We analyze over 1 million public checks of Twitter accounts from 2020 to 2023, enriched with 3.2 billion tweets from the contemporaneous 1% public stream. Collective suspicion spikes with platform crises, most sharply around the 2022 Musk-Twitter bot dispute. Checked accounts are older and more prolific, have more followers, and post promotional, political, and crypto content. Accounts that draw collective suspicion have higher bot scores and are more likely to be suspended. Bot-related public attention and Botometer activity are elevated during the same broad periods, although their short-run fluctuations are largely uncoupled. Public feedback focuses on first-person identity claims for humans, and evidence-based arguments citing posting rate, political content, and cross-account coordination for bots and cyborgs. Bot suspicion thus constitutes a mass, distributed form of platform auditing that tracks meaningful signals of automation, establishing audit-tool query logs as a novel lens on public responses to platform manipulation.