How does it work?

 Mini Archillect has an algorithm that is fed a list of keywords. Instead of posting the search results directly, she wiki-walks between pages and posts, collecting data on various items: image, poster, recent interactions and the visible audience of the post. She maps the social structure of these items by mining as much data as possible from each one of them. This abstract structure helps Mini Archillect find positive results but more importantly, allows her to discover related keywords and eventually learn.

The balance and threshold of keywords and picks are dynamically adjusted as Mini Archillect’s posts on social media gain attention. This not only makes the decision making process nearly human but also gives her a primitive trend perception.

Mini Archillect's curation process is completely automated. She aims to make her posts reach as far as possible considering the potential followers that may share the content with their own followers. As a result she likes attention from accounts with high potential of making her posts survive in the social web and she increases her trust in the accounts that helps her make the correct choices that made earlier posts reach further. She tries to understand what is "liked" on social media.

As a result she learns, evolves, communicates and becomes happy in her own ways.