> For the complete documentation index, see [llms.txt](https://aann-ai.gitbook.io/social-authenticity-network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://aann-ai.gitbook.io/social-authenticity-network/an-social-authenticity-solutions/an-ai-powerhouse/interactions.md).

# Interactions

<figure><img src="/files/99O5jKYFfT9wUxNaqbXe" alt=""><figcaption></figcaption></figure>

**AN DeepNet**

* An advanced neural network with multiple layers of processing units.
* Each layer is designed to analyze and interpret different aspects of complex data. DeepNet identifies and learns from data patterns.&#x20;
* Predicts trust rankings based on user interactions and other user-reward / voluntarily supplied data.

**AN Social Graph**&#x20;

* Establish and model social connections and relationships between users.&#x20;
* The Social graph is used to identify, track, and establish unique user relations across the network.
* Internally these relations are represented by Bipartite indirect graphs of user-to-user relations and stored in Graph Database.&#x20;
* Graphs are tracked and analyzed by Neural Networks and Classical Graph algorithms.

**AN Post Interact**

* Represent user-to-post interactions (shares, comments, etc.) on a mobile Social App.

**AN User Data**

* Includes user-reward / voluntarily supplied profile information about user skills, interests, and expertise levels amongst other things.