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Media Forensics Continues Unveiling the Twitter Propaganda Machine: 464 Accounts Identified in Digital Deception

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Griffith Sarah

Jun 24, 2024

Unmasking Digital Deception: Researchers Expose 464 Twitter Accounts in Coordinated Influence Campaign

Rwandan Spokesperson Yolanda Makolo and her boss Paul Kagame as powerhouse for their own media propagandists

Recent investigations have uncovered a sophisticated network of 464 accounts on X/Twitter, orchestrating a coordinated influence operation (CIO). Researchers meticulously inspected the social media information environment across various platforms, focusing on narratives likely targeted for manipulation. The study revealed distinct clusters of accounts, highlighting key participants and potential opinion leaders.


Key Findings

Clusters of Influence

The investigation identified two primary clusters:

  1. Pro-Rwanda Cluster: A smaller, tightly-knit group of highly active pro-Rwanda accounts, including influencers [@FelixMugenzi] and [@BahoNtaganira] This cluster aimed to undermine the credibility of Forbidden Stories, a collective of journalists.


  2. Forbidden Stories Cluster: A larger, more diffuse cluster containing Forbidden Stories (@FbdnStories) and several affiliated journalists, such as @SamuelBaker_B. This group promoted the investigative reporting by Forbidden Stories.


Criteria for Identifying Accounts

Researchers used stringent criteria to identify accounts involved in the campaign:

  • Shared either # RwandaClassified or # RPFonTop between May 13 and May 31, 2024.

  • Used at least two suspicious hashtags six or more times within the same period.

  • Posted original tweets with common characteristics (language, media sources, length, and hashtags).

  • Passed manual inspection to exclude accounts with substantial idiosyncratic content.


Data Collection and Analysis

The original data pull included all tweets mentioning # RwandaClassified or # RPFOnTop between May 13 and May 31, 2024, resulting in 149,246 messages from 5,537 accounts. Suspicious hashtags were identified based on frequency in messages from accounts sending at least ten messages during this period.


The top suspicious hashtags included:


Through further analysis, 610 accounts were identified as sharing two or more suspicious hashtags at least six times. After removing suspended accounts and applying additional hand-cleaning criteria, 464 accounts remained for the final analysis.


On June 1, 2024, researchers pulled the latest data, collecting up to 10,000 messages from each of the 463 remaining accounts, resulting in 787,261 posts.


Propaganda Tactics

The identified accounts predominantly followed a pattern of rapid publication, using AI-generated text and preferred hashtags. Following the release of Forbidden Stories' reporting, these accounts targeted the reporting itself (# RwandaClassified) and promoted Rwandan political figures and parties, such as Paul Kagame (# PKNiWowe) and the Rwandan Patriotic Front (# RPFOnTop). These tactics aimed to disrupt online discussions and flood social media with government propaganda.


The investigation into these 464 Twitter accounts highlights the extent and sophistication of coordinated influence operations.

 The smaller cluster (bottom left) is a tight-knit group of highly active pro-Rwanda accounts, including influencers @FelixMugenzi and @BahoNtaganira, aimed at undermining Forbidden Stories. The larger, more diffuse cluster (top right) includes Forbidden Stories (@FbdnStories) and affiliated journalists like @SamuelBaker_B, promoting the investigative reporting. Lines represent connections between accounts, highlighting key participants and potential opinion leaders within each cluster.

By employing media forensics and advanced analysis techniques, researchers were able to uncover a network dedicated to manipulating public perception and undermining credible journalism. As social media platforms continue to play a critical role in shaping public discourse, such studies are essential in identifying and countering the spread of disinformation.

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