People are Strange when you're a Stranger: Impact and Influence of Bots on Social Networks
This addresses the problem of bot influence and manipulation in social networks for researchers and platform designers, though it is incremental in exploring non-human-like bot strategies.
The study investigated whether a simple bot without human-like features could gain popularity and influence in a social network, finding that basic social probing allowed it to acquire relevance and drive user connectivity choices, while also revealing hidden social polarization and privacy concerns.
Bots are, for many Web and social media users, the source of many dangerous attacks or the carrier of unwanted messages, such as spam. Nevertheless, crawlers and software agents are a precious tool for analysts, and they are continuously executed to collect data or to test distributed applications. However, no one knows which is the real potential of a bot whose purpose is to control a community, to manipulate consensus, or to influence user behavior. It is commonly believed that the better an agent simulates human behavior in a social network, the more it can succeed to generate an impact in that community. We contribute to shed light on this issue through an online social experiment aimed to study to what extent a bot with no trust, no profile, and no aims to reproduce human behavior, can become popular and influential in a social media. Results show that a basic social probing activity can be used to acquire social relevance on the network and that the so-acquired popularity can be effectively leveraged to drive users in their social connectivity choices. We also register that our bot activity unveiled hidden social polarization patterns in the community and triggered an emotional response of individuals that brings to light subtle privacy hazards perceived by the user base.