Analyzing X mentions to uncover micro-clusters interfering in political campaigns: a case study during the Spanish elections

Abstract

Introduction: Coordinated influence campaigns on social networks pose a growing threat to democratic discourse, especially during electoral periods. This study investigates such efforts within political conversations during the Spanish regional elections of May 2023.

Methods: We analyzed a dataset of 345,000 messages posted on X (formerly Twitter) by 17,074 unique users. Using advanced quantitative techniques, we focused on the analysis of mentions to detect coordination patterns. We identified micro-clusters—groups of users engaging in synchronized messaging strategies—by tracking distribution lists and repeated amplification behaviors.

Results: Our findings reveal patterns of coordinated activity targeting political figures, journalists, and other influential actors. The Gephi-generated network maps visualize these micro-clusters and expose homophilic behavior and feedback loops that enhance the virality of messages.

Discussion: These results demonstrate the sophistication of digital tactics employed to manipulate political discourse. The study highlights the urgent need for effective detection mechanisms and regulatory frameworks to protect the integrity of public debate during electoral campaigns.