Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 87 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 13 tok/s Pro
GPT-5 High 16 tok/s Pro
GPT-4o 98 tok/s Pro
GPT OSS 120B 472 tok/s Pro
Kimi K2 210 tok/s Pro
2000 character limit reached

A random matrix perspective of cultural structure: groups or redundancies? (1803.04324v2)

Published 12 Mar 2018 in physics.soc-ph, cond-mat.stat-mech, and cs.CY

Abstract: Recent studies have highlighted interesting structural properties of empirical cultural states: collections of cultural traits sequences of real individuals. Matrices of similarity between individuals may be constructed from these states, allowing for further structural insights to be gained using concepts from random matrix theory, approach first exploited in this study. For generating random matrices that are appropriate as a structureless reference, we propose a null model that enforces, on average, the empirical occurrence frequency of each possible trait. With respect to this null model, the empirical matrices show deviating eigenvalues, which may be signatures of subtle cultural groups. However, they can conceivably also be artifacts of arbitrary redundancies between cultural variables. We first study this possibility in a highly simplified setting, using a toy model that enforces a certain level of redundancy in a minimally-biased way, in parallel with another toy model that enforces group structure. By analyzing and comparing cultural states generated with these toy models, we show that a deviating eigenvalue can indeed be a redundancy signature, which can be distinguished from a grouping signature by evaluating the uniformity of the entries of the respective eigenvector, as well as the uniformity-based compatibility with the null model. For empirical data, the eigenvector uniformities of all deviating eigenvalues are shown to be compatible with the null model, apparently suggesting that we are not dealing with genuine group structure. However, we demonstrate that some deviating eigenvalues might actually be due to authentic groups that are internally non-uniform. A generic procedure for distinguishing such groups from redundancy artifacts requires further research.

Citations (3)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.