scholarly journals Social network architecture and the maintenance of deleterious cultural traits

2011 ◽  
Vol 9 (70) ◽  
pp. 848-858 ◽  
Author(s):  
Sam Yeaman ◽  
Alana Schick ◽  
Laurent Lehmann
Keyword(s):  
Information Flow ◽  
Cultural Evolution ◽  
Network Architecture ◽  
Intrinsic Value ◽  
Analytical Models ◽  
Communications Technology ◽  
Considerable Research ◽  
Selective Elimination ◽  
Cultural Traits ◽  
Percolation Processes

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a ‘cultural load’ of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

scholarly journals Social network architecture and the tempo of cumulative cultural evolution

2020 ◽  
Author(s):  
Mauricio Cantor ◽  
Michael C. Chimento ◽  
Simeon Q. Smeele ◽  
Peng He ◽  
Danai Papageorgiou ◽  
...  
Keyword(s):  
Social Network ◽  
Population Size ◽  
Cultural Evolution ◽  
Network Architecture ◽  
Size Structure ◽  
Social Systems ◽  
Future Research ◽  
Transmission Mechanisms ◽  
Cultural Traits ◽  
Cumulative Cultural Evolution

AbstractThe ability to build upon previous knowledge—cumulative cultural evolution (CCE)—is a hallmark of human societies. While CCE depends on the interaction between social systems, cognition and the environment, there is increasing evidence that CCE is facilitated by larger and more structured societies. However, the relative importance of social network architecture as an additional factor shaping CCE remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while multilevel societies can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of CCE. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

scholarly journals Social network architecture and the tempo of cumulative cultural evolution

2021 ◽  
Vol 288 (1946) ◽  
pp. 20203107
Author(s):  
Mauricio Cantor ◽  
Michael Chimento ◽  
Simeon Q. Smeele ◽  
Peng He ◽  
Danai Papageorgiou ◽  
...  
Keyword(s):  
Social Network ◽  
Population Size ◽  
Cultural Evolution ◽  
Network Architecture ◽  
Size Structure ◽  
Social Systems ◽  
Future Research ◽  
Transmission Mechanisms ◽  
Cultural Traits ◽  
Cumulative Cultural Evolution

The ability to build upon previous knowledge—cumulative cultural evolution—is a hallmark of human societies. While cumulative cultural evolution depends on the interaction between social systems, cognition and the environment, there is increasing evidence that cumulative cultural evolution is facilitated by larger and more structured societies. However, such effects may be interlinked with patterns of social wiring, thus the relative importance of social network architecture as an additional factor shaping cumulative cultural evolution remains unclear. By simulating innovation and diffusion of cultural traits in populations with stereotyped social structures, we disentangle the relative contributions of network architecture from those of population size and connectivity. We demonstrate that while more structured networks, such as those found in multilevel societies, can promote the recombination of cultural traits into high-value products, they also hinder spread and make products more likely to go extinct. We find that transmission mechanisms are therefore critical in determining the outcomes of cumulative cultural evolution. Our results highlight the complex interaction between population size, structure and transmission mechanisms, with important implications for future research.

scholarly journals Crafting Efficient Neural Graph of Large Entropy

2019 ◽  
Author(s):  
Minjing Dong ◽  
Hanting Chen ◽  
Yunhe Wang ◽  
Chang Xu
Keyword(s):  
Information Flow ◽  
Network Architecture ◽  
High Performance ◽  
Global Information ◽  
High Quality ◽  
Network Pruning ◽  
Initial Network ◽  
Trade Offs ◽  
Graph Properties ◽  
Deep Cnn

Network pruning is widely applied to deep CNN models due to their heavy computation costs and achieves high performance by keeping important weights while removing the redundancy. Pruning redundant weights directly may hurt global information flow, which suggests that an efficient sparse network should take graph properties into account. Thus, instead of paying more attention to preserving important weight, we focus on the pruned architecture itself. We propose to use graph entropy as the measurement, which shows useful properties to craft high-quality neural graphs and enables us to propose efficient algorithm to construct them as the initial network architecture. Our algorithm can be easily implemented and deployed to different popular CNN models and achieve better trade-offs.

scholarly journals Cultural accumulation and improvement in online fan fiction

2020 ◽  
Author(s):  
Federico Pianzola ◽  
Alberto Acerbi ◽  
Simone Rebora
Keyword(s):  
Digital Media ◽  
Cultural Evolution ◽  
Harry Potter ◽  
Fan Fiction ◽  
Cumulative Culture ◽  
Cultural Systems ◽  
Cultural Traits ◽  
Cumulative Cultural Evolution ◽  
Cultural Evolution Theory ◽  
Digital Literary Studies

We analyse stories in Harry Potter fan fiction published on Archive of Our Own (AO3), using concepts from cultural evolution. In particular, we focus on cumulative cultural evolution, that is, the idea that cultural systems improve with time, drawing on previous innovations. In this study we examine two features of cumulative culture: accumulation and improvement. First, we show that stories in Harry Potter’s fan fiction accumulate cultural traits—unique tags, in our analysis—through time, both globally and at the level of single stories. Second, more recent stories are also liked more by readers than earlier stories. Our research illustrates the potential of the combination of cultural evolution theory and digital literary studies, and it paves the way for the study of the effects of online digital media on cultural cumulation.

scholarly journals The Uses and Abuses of Tree Thinking in Cultural Evolution

2021 ◽  
Author(s):  
Cara Evans ◽  
Simon J. Greenhill ◽  
Joseph Watts ◽  
Johann-Mattis List ◽  
Carlos A. Botero ◽  
...  
Keyword(s):  
Best Practices ◽  
Cultural Evolution ◽  
Cross Cultural ◽  
Tree Thinking ◽  
Phylogenetic Methods ◽  
Cultural Research ◽  
Cross Cultural Research ◽  
Cultural Traits ◽  
Lines Of Evidence ◽  
Over Time

Modern phylogenetic methods are increasingly being used to address questions about macro-level patterns in cultural evolution. These methods can illuminate the unobservable histories of cultural traits and identify the evolutionary drivers of trait-change over time, but their application is not without pitfalls. Here we outline the current scope of research in cultural tree thinking, highlighting a toolkit of best practices to navigate and avoid the pitfalls and ‘abuses’ associated with their application. We emphasise two principles that support the appropriate application of phylogenetic methodologies in cross-cultural research: researchers should (1) draw on multiple lines of evidence when deciding if and which types of phylogenetic methods and models are suitable for their cross-cultural data, and (2) carefully consider how different cultural traits might have different evolutionary histories across space and time. When used appropriately phylogenetic methods can provide powerful insights into the processes of evolutionary change that have shaped the broad patterns of human history.

scholarly journals Guttman Scale Analysis and its use to explain Cultural Evolution and Social Change

2019 ◽  
Author(s):  
Rochelle Forrester
Keyword(s):  
Social Change ◽  
Cultural History ◽  
Cultural Evolution ◽  
Natural World ◽  
Scale Analysis ◽  
Human Knowledge ◽  
Guttman Scale ◽  
Human Environment ◽  
Cultural Traits ◽  
Universal Pattern

Guttman scale analysis is a very useful tool to understand the evolution of societies. It shows the accumulation of cultural traits throughout history in various societies and that those cultural traits were usually accumulated in the same order. The results of studies, by Robert Carneiro and others, shows the accumulation of cultural traits is not random and indicates a universal pattern in cultural evolution. The universal pattern is caused by increasing human knowledge of the environment we live in. Human societies usually acquire this knowledge in the same order, with easier discoveries concerning the natural world being made earlier than more complex discoveries. This means human social and cultural history, usually follows a particular course, a course that is determined by the structure of the human environment.

scholarly journals Cross-correlations of American baby names

2015 ◽  
Vol 112 (26) ◽  
pp. 7943-7947 ◽  
Author(s):  
Paolo Barucca ◽  
Jacopo Rocchi ◽  
Enzo Marinari ◽  
Giorgio Parisi ◽  
Federico Ricci-Tersenghi
Keyword(s):  
Cultural Evolution ◽  
Human Activities ◽  
Quantitative Description ◽  
The United States ◽  
Digital Era ◽  
The People ◽  
Cultural Movements ◽  
Cross Correlations ◽  
Cultural Traits ◽  
The One

The quantitative description of cultural evolution is a challenging task. The most difficult part of the problem is probably to find the appropriate measurable quantities that can make more quantitative such evasive concepts as, for example, dynamics of cultural movements, behavioral patterns, and traditions of the people. A strategy to tackle this issue is to observe particular features of human activities, i.e., cultural traits, such as names given to newborns. We study the names of babies born in the United States from 1910 to 2012. Our analysis shows that groups of different correlated states naturally emerge in different epochs, and we are able to follow and decrypt their evolution. Although these groups of states are stable across many decades, a sudden reorganization occurs in the last part of the 20th century. We unambiguously demonstrate that cultural evolution of society can be observed and quantified by looking at cultural traits. We think that this kind of quantitative analysis can be possibly extended to other cultural traits: Although databases covering more than one century (such as the one we used) are rare, the cultural evolution on shorter timescales can be studied due to the fact that many human activities are usually recorded in the present digital era.

scholarly journals How cultural evolution can inform the science of science communication—and vice versa

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Theiss Bendixen
Keyword(s):  
Cultural Evolution ◽  
Real World ◽  
Behavioral Change ◽  
Science Communication ◽  
Accurate Information ◽  
Communication Research ◽  
Science Of Science ◽  
Real World Setting ◽  
Cultural Traits ◽  
Cultural Evolutionary

AbstractCultural evolution research is the study of how cultural traits (e.g., beliefs and behavioral patterns) stabilize, change and diffuse in populations, and why some cultural traits are more “attractive” (i.e., more likely to spread) than others. As such, cultural evolution is highly relevant for the emerging “science of science communication” (SSC) in that it can help organize and guide the study of science communication efforts aimed at spreading scientifically accurate information and inspiring behavioral change. Here, I synthesize insights and theory from cultural evolution with central findings and concepts within the SSC with the aim of highlighting the inherent, but underexplored, consilience between these two fields. I demonstrate how cultural evolution can serve as an unifying framework for the SSC and how, conversely, science communication can serve as a fertile testing ground for applying, exploring, and advancing cultural evolutionary theory in a real-world setting that matters. Lastly, I highlight merits and limitations of previous applications of cultural evolution to science communication and conclude with some particularly outstanding questions that emerge at the intersection between cultural evolution and science communication research.

scholarly journals Deep Convolutional Neural Networks with Merge-and-Run Mappings

2018 ◽  
Author(s):  
Liming Zhao ◽  
Mingjie Li ◽  
Depu Meng ◽  
Xi Li ◽  
Zhaoxiang Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Information Flow ◽  
Building Block ◽  
Network Architecture ◽  
Time Complexity ◽  
Residual Network ◽  
Deep Convolutional Neural Networks ◽  
Testing Error ◽  
Simple Network

A deep residual network, built by stacking a sequence of residual blocks, is easy to train, because identity mappings skip residual branches and thus improve information flow. To further reduce the training difficulty, we present a simple network architecture, deep merge-and-run neural networks. The novelty lies in a modularized building block, merge-and-run block, which assembles residual branches in parallel through a merge-and-run mapping: average the inputs of these residual branches (Merge), and add the average to the output of each residual branch as the input of the subsequent residual branch (Run), respectively. We show that the merge-and-run mapping is a linear idempotent function in which the transformation matrix is idempotent, and thus improves information flow, making training easy. In comparison with residual networks, our networks enjoy compelling advantages: they contain much shorter paths and the width, i.e., the number of channels, is increased, and the time complexity remains unchanged. We evaluate the performance on the standard recognition tasks. Our approach demonstrates consistent improvements over ResNets with the comparable setup, and achieves competitive results (e.g., 3.06% testing error on CIFAR-10, 17.55% on CIFAR-100, 1.51% on SVHN). 

scholarly journals The uses and abuses of tree thinking in cultural evolution

2021 ◽  
Vol 376 (1828) ◽  
Author(s):  
Cara L. Evans ◽  
Simon J. Greenhill ◽  
Joseph Watts ◽  
Johann-Mattis List ◽  
Carlos A. Botero ◽  
...  
Keyword(s):  
Best Practices ◽  
Cultural Evolution ◽  
Cross Cultural ◽  
Theme Issue ◽  
Tree Thinking ◽  
Phylogenetic Methods ◽  
Cultural Research ◽  
Cross Cultural Research ◽  
Cultural Traits ◽  
Lines Of Evidence

Modern phylogenetic methods are increasingly being used to address questions about macro-level patterns in cultural evolution. These methods can illuminate the unobservable histories of cultural traits and identify the evolutionary drivers of trait change over time, but their application is not without pitfalls. Here, we outline the current scope of research in cultural tree thinking, highlighting a toolkit of best practices to navigate and avoid the pitfalls and ‘abuses' associated with their application. We emphasize two principles that support the appropriate application of phylogenetic methodologies in cross-cultural research: researchers should (1) draw on multiple lines of evidence when deciding if and which types of phylogenetic methods and models are suitable for their cross-cultural data, and (2) carefully consider how different cultural traits might have different evolutionary histories across space and time. When used appropriately phylogenetic methods can provide powerful insights into the processes of evolutionary change that have shaped the broad patterns of human history. This article is part of the theme issue ‘Foundations of cultural evolution'.

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