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Twitter bots are a controversial element of the platform, and their negativeimpact is well known. In the field of scientific communication, they have beenperceived in a more positive light, and the accounts that serve as feedsalerting about scientific publications are quite common. However, despite beingaware of the presence of bots in the dissemination of science, no large-scaleestimations have been made nor has it been evaluated if they can trulyinterfere with altmetrics. Analyzing a dataset of 3,744,231 papers publishedbetween 2017 and 2021 and their associated 51,230,936 Twitter mentions, ourgoal was to determine the volume of publications mentioned by bots and whetherthey skew altmetrics indicators. Using the BotometerLite API, we categorizedTwitter accounts based on their likelihood of being bots. The results showedthat 11,073 accounts (0.23% of total users) exhibited automated behavior,contributing to 4.72% of all mentions. A significant bias was observed in theactivity of bots. Their presence was particularly pronounced in disciplinessuch as Mathematics, Physics, and Space Sciences, with some specialties evenexceeding 70% of the tweets. However, these are extreme cases, and the impactof this activity on altmetrics varies by speciality, with minimal influence inArts & Humanities and Social Sciences. This research emphasizes the importanceof distinguishing between specialties and disciplines when using Twitter as analtmetric.

The Botization of Science? Large-scale study of the presence and impact of Twitter bots in science dissemination