Many users on social media prefer to stay anonymous and use creative or emotional nicknames instead of real names. Examples include:
💬 Lonely Guy, Butterfly’s Dream, Colorful Heart, Strong Commander
Our earlier systems could only make gender predictions based on known real names. These types of aliases couldn’t be analyzed with traditional methods, which created a major limitation—especially when working with social media data.
To solve this, we’ve developed a dedicated AI model that overcomes this challenge.
Our new algorithm analyzes display names and usernames that may include nicknames, phrases, or emotional expressions. It evaluates:
Thanks to this approach, the model can make gender predictions even when no real name is present.
This feature is currently available as a manual checkbox option in our Excel/CSV upload tool.
When uploading your file, if you believe your data contains usernames or nicknames, simply check the box labeled:
"My data contains social media nicknames such as ‘Lonely guy’ or ‘Colorful butterfly’. My priority is to determine gender and country from this data. It doesn’t matter whether the name belongs to a real person."
You should check this box if:
Examples:
| Display Name / Username | Predicted Gender |
|---|---|
| butterfly.dream89 | Female |
| strongcommander34 | Male |
| rainbow.heart | Female |
| lone_eagle | Male |
🆓 You also get 200 free queries per day with your account!
We will soon extend this feature to other integrations:
Working with incomplete or anonymous data has always been a challenge in:
With this new AI model, you can now analyze those datasets more effectively—even when names are ambiguous or missing.
Real names are no longer required for accurate gender predictions. Our updated AI algorithm understands the meaning and emotional tone behind usernames and aliases—unlocking new possibilities in data analysis.
With a simple checkbox in our Excel/CSV upload tool, you can start leveraging this powerful feature today.