Creator AI Recognition Detection

We currently support 18 global mainstream social media platforms, including Instagram, TikTok, YouTube, Twitter, Facebook, Snapchat, etc. We have made in-depth optimizations for YouTube, Instagram, and TikTok, which are commonly used by cross-border e-commerce platforms, and can identify the brushing patterns in different regions such as Southeast Asia, Europe and the United States.

Our system will analyze the historical growth curve of Internet celebrity accounts. The follower growth of normal accounts should be relatively stable. If the follower growth exceeds 300 people/hour within 48 hours, or there is "pulse growth" (short-term surge followed by stagnation), the system will automatically mark it as high risk. We will also make a comprehensive judgment based on the frequency of content release and changes in quality.

Yes, our third-generation AI detection engine is optimized for manually active fake fans. By analyzing multi-dimensional data such as fans' interaction patterns, comment semantic quality, device fingerprints, etc., it can identify fake fan accounts that simulate real-life behavior with an accuracy rate of 88.4%. The system also detects the relevance and depth of comment content and identifies "universal comment" templates.

Not necessarily. We will first analyze the operating status and content publishing frequency of the influencer on each platform. If a platform basically does not update content, the data difference is normal. However, if the influencer remains active on multiple platforms, the difference in the number of fans exceeds 70%, and it cannot be explained by the characteristics of the platform, then there may be a single platform brushing behavior. Our system will conduct cross-platform correlation analysis to provide more accurate judgments.

We will comprehensively analyze factors such as the content language, cultural background, and partner brands of influencers to determine the rationality of the geographical distribution of fans. For example, if 90% of an English beauty blogger's fans are from Asia and she has never published content related to Asia, this is abnormal. But for globally renowned influencers, it is normal to have fans distributed in multiple regions. Our algorithm will dynamically adjust the judgment criteria based on the influence level and content characteristics of the influencer.