> For the complete documentation index, see [llms.txt](https://docs.neighbourhoods.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.neighbourhoods.network/powered-by-the-reputation-interchange/reputation-domain-specific-language-dsl.md).

# Architecture: The Cultural Computer

Using the Social Sensemaker involves making sense of Social Data through "cultural computation" that analyzes it. Sharing this data and calculated Scores evolves into what we call a neighbourhood. It's easiest to understand the Sensemakere by looking at how it works on one and then two computers.  

## Cultural Computer

Social data can be sourced from traditional web services or dWeb apps. Scores hold the results of these computations, while tying them to the sources of the raw social data with full provenance. This also makes auditing possible.  

![](/files/ahahwjH6vRYCU4BvjR0x)

Scores can be fed back into the cultural computer to chain, stack, and complexify insights. 

## Shared Cultural Computation

Two people can share and cross-verify calculated scores. Context is preserved by including metadata about the computation and its raw data sources.  

![](/files/dSD1P2uG45KcmceIphOO)


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