BotSim: Mitigating The Formation Of Conspiratorial Societies with Useful Bots

TL;DR

This paper introduces BotSim, an agent-based model demonstrating how useful bots like Info-Correction and Good Bots can mitigate the spread of conspiracy theories in social networks, highlighting the effectiveness of proactive messaging.

Contribution

The study presents BotSim, a novel simulation framework analyzing the impact of different types of beneficial bots on reducing conspiratorial societies in social media environments.

Findings

Good Bots are more efficient than Info-Correction Bots.

Proactive messaging is more resource-effective than reactive correction.

Uncontrolled Bad Bots can foster conspiratorial societies.

Abstract

Societies can become a conspiratorial society where there is a majority of humans that believe, and therefore spread, conspiracy theories. Artificial intelligence gave rise to social media bots that can spread conspiracies in an automated fashion. Currently, organizations combat the spread of conspiracies through manual fact-checking processes and the dissemination of counter-narratives. However, the effects of harnessing the same automation to create useful bots are not well explored. To address this, we create BotSim, an Agent-Based Model of a society in which useful bots are introduced into a small world network. These useful bots are: Info-Correction Bots, which correct bad information into good, and Good Bots, which put out good messaging. The simulated agents interact through generating, consuming and propagating information. Our results show that, left unchecked, Bad Bots can create a conspiratorial society, and this can be mitigated by either Info-Correction Bots or Good Bots; however, Good Bots are more efficient and sustainable than Info-Correction Bots . Proactive good messaging is more resource-effective than reactive information correction. With our observations, we expand the concept of bots as a malicious social media agent towards automated social media agent that can be used for both good and bad purposes. These results have implications for designing communication strategies to maintain a healthy social cyber ecosystem.