The study explores the evolution of bot accusations on Twitter over time. In the early years (before 2017), users were mainly accused of being bots when they exhibited explicit signs of automation, such as spamming repetitive content or reaching follow/rate limits. However, since 2017, the meaning of bot accusations has shifted significantly.
The authors find that bot accusations are now predominantly used as a dehumanizing insult, questioning the intelligence and right to express opinions of the accused users. These accusations often occur in the context of polarizing political debates around topics like elections, COVID-19, or Brexit.
The study also shows a discrepancy between the bot definitions internalized by Twitter users and the operationalization of bots in academic bot detection methods like Botometer. While accounts accused of being bots had high Botometer scores in the early years, this correlation disappeared in later years as the accusations became more of a political insult rather than a reflection of actual automation.
The findings have important implications for researchers interested in bot detection, as bot accusations on social media should not be naively used as a signal or ground-truth data for such methods. The study also highlights the need for future research on the impact of these dehumanizing bot accusations on individuals and how they can be effectively countered.
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