# A Socio-Informatic Approach to Automated Account Classification on Social Media

## TL;DR

This paper introduces a socio-informatic feature to enhance machine learning algorithms for detecting automated social media accounts, significantly improving classification accuracy.

## Contribution

It presents a novel socio-informatic feature that, when combined with existing methods, advances automated account classification on social media.

## Key findings

- Improved bot detection accuracy with the new feature.
- Enhanced machine learning performance in social media account classification.
- Validation of the feature's effectiveness through experimental results.

## Abstract

Automated accounts on social media have become increasingly problematic. We propose a key feature in combination with existing methods to improve machine learning algorithms for bot detection. We successfully improve classification performance through including the proposed feature.