社会老龄化与高阶互动:社会选择性可提高老年人传播知识的能力。

IF 5.4 2区 生物学 Q1 BIOLOGY
Matthew J Hasenjager, Nina H Fefferman
{"title":"社会老龄化与高阶互动:社会选择性可提高老年人传播知识的能力。","authors":"Matthew J Hasenjager, Nina H Fefferman","doi":"10.1098/rstb.2022.0461","DOIUrl":null,"url":null,"abstract":"<p><p>In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.</p>","PeriodicalId":19872,"journal":{"name":"Philosophical Transactions of the Royal Society B: Biological Sciences","volume":"379 1916","pages":"20220461"},"PeriodicalIF":5.4000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513644/pdf/","citationCount":"0","resultStr":"{\"title\":\"Social ageing and higher-order interactions: social selectiveness can enhance older individuals' capacity to transmit knowledge.\",\"authors\":\"Matthew J Hasenjager, Nina H Fefferman\",\"doi\":\"10.1098/rstb.2022.0461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.</p>\",\"PeriodicalId\":19872,\"journal\":{\"name\":\"Philosophical Transactions of the Royal Society B: Biological Sciences\",\"volume\":\"379 1916\",\"pages\":\"20220461\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513644/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Philosophical Transactions of the Royal Society B: Biological Sciences\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1098/rstb.2022.0461\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/10/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Philosophical Transactions of the Royal Society B: Biological Sciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1098/rstb.2022.0461","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/10/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

在长寿生物中,经验会随着年龄的增长而积累,因此年长个体可能会成为生态和社会知识的宝库。这些知识通常是有益的,并能通过社会传播而扩散,因此人们期望老龄个体能保持良好的社会融合。然而,社会老龄化涉及多个过程,这些过程会以复杂的方式调节年龄与社会连通性之间的关系。我们建立了一个生成模型,以探索社会老龄化如何推动社会网络地位的变化,以及如何塑造老年人向他人传播知识的能力。我们进一步采用新颖的超网络分析,捕捉高阶互动(即涉及≥ 3 个参与者),以揭示年龄与社会性之间的潜在关系,而传统的二元网络可能会忽略这一点。我们发现,在我们的模拟中,年龄较大的个体有效地促进了各种情况下的传播,尤其是当传播类似于复杂的传染或当社会选择性(即关键关系的优先化)随着年龄的增长而迅速出现时。这些模式的形成是由于在多个群体中共同出现的年长伙伴形成了紧密的联系,从而加强了彼此传播知识的能力。我们的研究结果为未来的实证工作提出了关键途径,并说明了超网络在推进社会行为研究中的应用。本文是讨论会议议题 "利用自然人群了解年龄与社会 "的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social ageing and higher-order interactions: social selectiveness can enhance older individuals' capacity to transmit knowledge.

In long-lived organisms, experience can accumulate with age, such that older individuals may act as repositories of ecological and social knowledge. Such knowledge is often beneficial and can spread via social transmission, leading to the expectation that ageing individuals will remain socially well-integrated. However, social ageing involves multiple processes that modulate the relationship between age and social connectivity in complex ways. We developed a generative model to explore how social ageing may drive changes in social network position and shape older individuals' capacity to transmit knowledge to others. We further employ novel hypernetwork analyses that capture higher-order interactions (i.e. involving ≥ 3 participants) to reveal potential relationships between age and sociality that conventional dyadic networks may overlook. We find that older individuals in our simulations effectively facilitate transmission across a range of scenarios, especially when transmission resembles a complex contagion or when social selectivity (i.e. prioritization of key relationships) rapidly emerges with age. These patterns result from the formation of tight-knit sets of older associates that co-occur in multiple groups, thereby reinforcing one another's capacity to transmit knowledge. Our findings suggest key avenues for future empirical work and illustrate the use of hypernetworks in advancing the study of social behaviour.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
11.80
自引率
1.60%
发文量
365
审稿时长
3 months
期刊介绍: The journal publishes topics across the life sciences. As long as the core subject lies within the biological sciences, some issues may also include content crossing into other areas such as the physical sciences, social sciences, biophysics, policy, economics etc. Issues generally sit within four broad areas (although many issues sit across these areas): Organismal, environmental and evolutionary biology Neuroscience and cognition Cellular, molecular and developmental biology Health and disease.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信