Through BotAmp, a new tool from the Botometer family that anyone with a Twitter account can use, we have found that the presence of automated activity is not evenly distributed. For instance, the discussion about cryptocurrencies tends to show more bot activity than the discussion about cats. Therefore, whether the overall prevalence is 5% or 20% makes little difference to individual users; their experiences with these accounts depend on whom they follow and the topics they care about.
Recent evidence suggests that inauthentic accounts might not be the only culprits responsible for the spread of misinformation, hate speech, polarization, and radicalization. These issues typically involve many human users. For instance, our analysis shows that misinformation about COVID-19 was disseminated overtly on both Twitter and Facebook by verified, high-profile accounts.
Even if it were possible to precisely estimate the prevalence of inauthentic accounts, this would do little to solve these problems. A meaningful first step would be to acknowledge the complex nature of these issues. This will help social media platforms and policymakers develop meaningful responses.
Kai-Cheng Yang is a doctoral student in informatics at Indiana University. Filippo Menczer is a professor of informatics and computer science at Indiana University.