Cultural Algebra

This is an attemp to apply some algebra concepts to cultural studies.

This project uses the Murdock Ethnographic Atlas Data set as a description of each cultures and turn to create a algebraic multi-dimensional space, where is culture is represented as a vector of all their political, economic, kinship, etc. features to calculate similarity among cultures as the cosine distance between vectors.

To see the whole analysis in detail, please click on Full Cultural Algebra analysis

TDLR

• Load an clean datasets
• Apply one hot encoding to categorical variables
• Merge with ordinal and numeric variables
• Normalize values
• Create a sparce matrix of Cosine distance values between ethnic groups
• Use the matrix to get the most similar cultures
• Use the matrix to build a graph model, where close cultures create links between them
• Apply dimensionality reduction to visualy map the cultural space usin Tsne and PCA
• Use clustering algorithms to try to group ethnic groups
• Compare cluster with family and geographical relations

Sample of dimensional space and cluster strategies

Author

@Pippo Ramos

Tech Stack

• Python 3.8
• Jupyter notebook
• Pandas
• Numpy
• Scklearn
• NetworkX