Arming the public with artificial intelligence to counter social bots

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2019-02-06

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Abstract

The increased relevance of social media in our daily life has been ac- companied by eorts to manipulate online conversations and opinions. Deceptive social bots | automated or semi-automated accounts designed to impersonate humans | have been successfully exploited for these kinds of abuse. Researchers have responded by developing AI tools to arm the public in the ght against social bots. Here we review the literature on dierent types of bots, their impact, and detection methods. We use the case study of Botometer, a popular bot detection tool developed at Indiana University, to illustrate how people interact with AI countermea- sures. A user experience survey suggests that bot detection has become an integral part of the social media experience for many users. However, barriers in interpreting the output of AI tools can lead to fundamental misunderstandings. The arms race between machine learning methods to develop sophisticated bots and eective countermeasures makes it neces- sary to update the training data and features of detection tools. We again use the Botometer case to illustrate both algorithmic and interpretabil- ity improvements of bot scores, designed to meet user expectations. We conclude by discussing how future AI developments may aect the ght between malicious bots and the public.

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This record is for a(n) postprint of an article published in Human Behavior and Emerging Technologies on 2019-02-06; the version of record is available at https://doi.org/10.1002/hbe2.115.

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Yang, Kaicheng, et al. "Arming the public with artificial intelligence to counter social bots." Human Behavior and Emerging Technologies, vol. 1, no. 1, pp. 48-61, 2019-02-06, https://doi.org/10.1002/hbe2.115.

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Human Behavior and Emerging Technologies

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