Introduction to Trust and Safety

At TRP.RED, we are committed to maintaining a safe and secure online environment for our users, where they can trust that their content is protected from malicious activities. We understand the importance of transparency in fostering trust, and we are dedicated to keeping our users informed about the various threats they might face, including spam, botnets, and potential international interference.

Our Trust and Safety team vigilantly monitors the platform to detect and mitigate any adverse activities. This comprehensive report highlights our efforts to combat these threats, providing insights into the trends, challenges, and successes we have experienced in our mission to safeguard user content.

In this report, we cover the following topics:

1. Spam: Our team's proactive approach to identifying and eliminating spam content on the platform, as well as the measures taken to prevent future occurrences.
2. Botnets: An overview of our strategies for detecting and dismantling botnets operating within the platform, and the steps we are taking to counter their evolving tactics.
3. International Interference: Our ongoing efforts to identify and address attempts at international interference with user content, including collaboration with authorities and other platforms to share information and best practices.

We believe that transparency and open communication are vital to building trust with our users. Through this report, we aim to provide you with a clear understanding of the work being done by our Trust and Safety team to protect your content and ensure a safe online experience.

We encourage you to read through the report and learn more about our ongoing initiatives. As always, we welcome your feedback on our Trust and Safety Tribe and suggestions for improvement, as we continue to enhance the security and integrity of our platform together.

---

During our analysis we found that there was a non-zero amount of bot and AI interference with our daily operations. The stats break down as such:

• 87% of our users showed organic interactions.
• Based on our language modelling, 75% of all posts are natural, non-generated content.
• 12% of users showed either botnet like tendencies, or failed basic natural language algorithm testing.

To identify and apprehend spam bots, the Trust and Safety team has leveraged advanced machine learning algorithms, coupled with extensive data analysis. By analyzing patterns of user behavior and communication, they have been able to pinpoint irregularities and anomalies that typically characterize spam bots. In addition to this, the team has also employed human expertise to validate and confirm their findings, ensuring a high level of accuracy in their efforts to eradicate spam from our platform.

The valuable data collected from these successful apprehensions has been instrumental in the creation of our new and improved spam filter. By using this real-world, spam-related data, our team of engineers and data scientists have been able to develop a more accurate and robust spam detection system. This new filter is equipped with the ability to adapt and learn from the latest spamming techniques, ensuring that it remains effective against the ever-evolving threat of spam bots.

As a result of our Trust and Safety team's tireless efforts, our platform is now more secure and user-friendly than ever before. The integration of the improved spam filter into our system serves as a testament to our ongoing commitment to providing a safe and enjoyable experience for all users. We are confident that these advancements will enable us to continue our fight against spam and maintain the highest standards of trust and safety on our platform.

Over the next few hours, we will be releasing our reports of samples of users that ranked highest with our algorithms, in an effort to maintain transparency and ensure the trust and confidence of our community. Please stay tuned.

---