Bots Election: Unveiling the complex network of social botnets

Abstract With the exponential growth of bots surpassing the near saturation of genuine users, a large socio-bot network has emerged. Botnets have evolved to exhibit significant social properties through their interactions with humans. This network has empowered bots with capabilities that cannot be observed locally; therefore, this study advocates examining bots as a complex network akin to human social networks. In our case study of Farsi Twitter users during Iran's 2021 presidential election, 71.2% of the users were identified as bots. By isolating the botnet, we analyzed the distinctions between bots and genuine users within complex networks, revealing a more robust, efficient, and controllable structure for information dissemination. To explore how following and retweeting actions influence each other, we classified bots based on their actions and examined the roles of each classification, the differences between the functional and structural core, and the impact of non-common bots on network controllability and regime transitions.Additionally, we observed how the activity of bots is limited within both the functional core and the entire system. Politically, our findings indicated that despite the candidates' use of bot accounts, political figures did not play a crucial role in controlling the botnet. We further explored the interactions between opposing political biases and the role of non-biased bots in bridging political divides and forming echo chambers.