Manipulating Twitter Through Deletions

TL;DR

This study provides a large-scale analysis of Twitter deletions, revealing abusive behaviors that manipulate content visibility and ranking, which are often hidden from public APIs.

Contribution

It offers the first comprehensive examination of deletion patterns on Twitter, uncovering new abuse tactics involving large-scale deletions and coordinated activities.

Findings

Over a billion deletions analyzed from 11 million accounts

Identification of abuse behaviors that bypass content limits

Revealed manipulation of ranking algorithms through coordinated actions

Abstract

Research into influence campaigns on Twitter has mostly relied on identifying malicious activities from tweets obtained via public APIs. These APIs provide access to public tweets that have not been deleted. However, bad actors can delete content strategically to manipulate the system. Unfortunately, estimates based on publicly available Twitter data underestimate the true deletion volume. Here, we provide the first exhaustive, large-scale analysis of anomalous deletion patterns involving more than a billion deletions by over 11 million accounts. We find that a small fraction of accounts delete a large number of tweets daily. We also uncover two abusive behaviors that exploit deletions. First, limits on tweet volume are circumvented, allowing certain accounts to flood the network with over 26 thousand daily tweets. Second, coordinated networks of accounts engage in repetitive likes and unlikes of content that is eventually deleted, which can manipulate ranking algorithms. These kinds of abuse can be exploited to amplify content and inflate popularity, while evading detection. Our study provides platforms and researchers with new methods for identifying social media abuse.