  During the COVID-19 pandemic, the proliferation of misinformation on social
media has been rapidly increasing. Automated Bot authors are believed to be
significant contributors of this surge. It is hypothesized that Bot authors
deliberately craft online misinformation aimed at triggering and exploiting
human cognitive biases, thereby enhancing tweet engagement and persuasive
influence. This study investigates this hypothesis by studying triggers of
biases embedded in Bot-authored misinformation and comparing them with their
counterparts, Human-authored misinformation. We complied a Misinfo Dataset that
contains COVID-19 vaccine-related misinformation tweets annotated by author
identities, Bots vs Humans, from Twitter during the vaccination period from
July 2020 to July 2021. We developed an algorithm to computationally automate
the extraction of triggers for eight cognitive biase. Our analysis revealed
that the Availability Bias, Cognitive Dissonance, and Confirmation Bias were
most commonly present in misinformation, with Bot-authored tweets exhibiting a
greater prevalence, with distinct patterns in utilizing bias triggers between
Humans and Bots. We further linked these bias triggers with engagement metrics,
inferring their potential influence on tweet engagement and persuasiveness.
Overall, our findings indicate that bias-triggering tactics have been more
influential on Bot-authored tweets than Human-authored tweets. While certain
bias triggers boosted engagement for Bot-authored tweets, some other bias
triggers unexpectedly decreased it. Conversely, triggers of most biases
appeared to be unrelated to the engagement of Human-authored tweets. Our work
sheds light on the differential utilization and effect of persuasion strategies
between Bot-authored and Human-authored misinformation from the lens of human
biases, offering insights for the development of effective counter-measures.
