Abstract:

When we replicate cultural artifacts, we transform them. But we are also selective when choosing which artifacts to copy in the first place. This talk explores these two components of cultural evolution (transformation and selection) within one awesome dataset: digital images from an online community, where users can choose images from the community board to mutate and can post their new creations back to the board. I find that the number of unique contributors in an image's direct lineage leads to higher image complexity, controlling for the image's age. Users also tend to select images to work on which have a higher community rating. These results show that cultural transformation (iterated learning, cultural attraction theory) and selection (social learning theory) can and should be brought together for a full understanding of cultural evolution in a given domain. This is a new project and suggestions for further analyses are highly encouranged!

Contact: 

Postdoc Vanessa Ferdinand, Santa Fe Institute

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