The rise of social bots

TLDR

The Turing test, originally designed to distinguish human from algorithmic behavior, has become increasingly relevant as social media platforms enable software agents to mimic humans, raising concerns about the uncertain prevalence of social bots and their potential for harmful influence. The paper examines the traits of sophisticated social bots and their threat to online ecosystems and society. The authors review Twitter bot detection methods that exploit content, network, sentiment, and temporal activity patterns to distinguish synthetic from human behavior.

Abstract

The Turing test aimed to recognize the behavior of a human from that of a computer algorithm. Such challenge is more relevant than ever in today's social media context, where limited attention and technology constrain the expressive power of humans, while incentives abound to develop software agents mimicking humans. These social bots interact, often unnoticed, with real people in social media ecosystems, but their abundance is uncertain. While many bots are benign, one can design harmful bots with the goals of persuading, smearing, or deceiving. Here we discuss the characteristics of modern, sophisticated social bots, and how their presence can endanger online ecosystems and our society. We then review current efforts to detect social bots on Twitter. Features related to content, network, sentiment, and temporal patterns of activity are imitated by bots but at the same time can help discriminate synthetic behaviors from human ones, yielding signatures of engineered social tampering.