Mnemonic convergence in social networks: The emergent properties of cognition at a collective level
Mnemonic convergence in social networks: The emergent properties of cognition at a collective level
复制标题
DOI：
10.1073/pnas.1525569113
复制
发表时间：
2016-07-19
影响因子：
11.1
通讯作者：
Geana, Andra
中科院分区：
文献类型：
--
作者：
Coman, Alin;Momennejad, Ida;Geana, Andra
共同记忆、信仰和规范的发展是人类社区的基本特征。人们认为，这些紧急结果的发生是由于信息共享和记忆更新的动态系统，而这从根本上取决于沟通。在这里，我们报告的结果在实验室创建的社区集体记忆的形成。我们在14个10人的社区中，通过一系列实时的、以计算机为媒介的互动来操纵会话网络结构。结果表明，记忆收敛，衡量社区成员的记忆之间的重叠程度，是由个人层面的信息处理现象和会话回忆过程中创建的会话社会网络结构的影响。通过研究实验室创建的社交网络，我们展示了大规模的社会现象（即，集体记忆）可以从微观级局部动态（即，记忆强化和抑制效应）。本文提出的社会互动主义的方法点在社交网络中传播信息的最佳策略，并提供了一个框架，测量和锻造集体记忆的个人社区。
The development of shared memories, beliefs, and norms is a fundamental characteristic of human communities. These emergent outcomes are thought to occur owing to a dynamic system of information sharing and memory updating, which fundamentally depends on communication. Here we report results on the formation of collective memories in laboratory-created communities. We manipulated conversational network structure in a series of real-time, computer-mediated interactions in fourteen 10-member communities. The results show that mnemonic convergence, measured as the degree of overlap among community members' memories, is influenced by both individual-level information-processing phenomena and by the conversational social network structure created during conversational recall. By studying laboratory-created social networks, we show how large-scale social phenomena (i.e., collective memory) can emerge out of microlevel local dynamics (i.e., mnemonic reinforcement and suppression effects). The social-interactionist approach proposed herein points to optimal strategies for spreading information in social networks and provides a framework for measuring and forging collective memories in communities of individuals.