Deploying South African Social Honeypots on Twitter

TL;DR

This paper presents the deployment of South African social honeypots on Twitter to identify low-quality political users, emphasizing honeypots as tools for capturing low-quality users rather than detecting bots, resulting in a list of 288 such users.

Contribution

It introduces localized honeypot techniques for Twitter in South Africa and clarifies their role in capturing low-quality users rather than detecting bots.

Findings

Generated 288 low-quality political users on Twitter.

Distinguished honeypots from bot detection methods.

Proposed techniques for local social honeypot deployment.

Abstract

Inspired by the simple, yet effective, method of tweeting gibberish to attract automated social agents (bots), we attempt to create localised honeypots in the South African political context. We produce a series of defined techniques and combine them to generate interactions from users on Twitter. The paper offers two key contributions. Conceptually, an argument is made that honeypots should not be confused for bot detection methods, but are rather methods to capture low-quality users. Secondly, we successfully generate a list of 288 local low quality users active in the political context.