The Rise of Social Bots

TL;DR

This paper discusses the rise of social bots in social media, their characteristics, potential threats, and current detection methods based on behavioral signatures to distinguish them from humans.

Contribution

It provides a comprehensive review of modern social bots, their impact on online ecosystems, and summarizes current detection techniques utilizing behavioral features.

Findings

Social bots mimic human behavior in content, network, sentiment, and activity patterns.

Detection methods leverage behavioral signatures to identify synthetic social media activity.

Social bots pose threats such as persuasion, deception, and misinformation.

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.