• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining >Socialization and trust formation: A mutual reinforcement? An exploratory analysis in an online virtual setting
【24h】

Socialization and trust formation: A mutual reinforcement? An exploratory analysis in an online virtual setting

机译：社会化和信任形成：相互加强？在线虚拟环境中的探索性分析

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Social interactions preceding and succeeding trust formation can be significant indicators of formation of trust in online social networks. In this research we analyze the social interaction trends that lead and follow formation of trust in these networks. This enables us to hypothesize novel theories responsible for explaining formation of trust in online social settings and provide key insights. We find that a certain level of socialization threshold needs to be met in order for trust to develop between two individuals. This threshold differs across persons and across networks. Once the trust relation has developed between a pair of characters connected by some social relation (also referred to as a character dyad), trust can be maintained with a lower rate of socialization. Our first set of experiments is the relationship prediction problem. We predict the emergence of a social relationship like grouping, mentoring and trading between two individuals over a period of time by looking at the past characteristics of the network. We find that features related to trust have very little impact on this prediction. In the final set of experiments, we predict the formation of trust between individuals by looking at the topographical and semantic social interaction features between them. We generate three semantic dimensions for this task which can be recomputed with an observed social variable (say grouping) to create a new semantic social variable. In this endeavor, we successfully show that, including features related to socialization, gives us an approximate increase of 4–9% accuracy for trust relationship predictions.
机译：信任形成之前和之后的社交互动可能是在线社交网络中信任形成的重要指标。在这项研究中，我们分析了在这些网络中导致和遵循信任形成的社会互动趋势。这使我们能够假设新颖的理论来解释在线社交环境中信任的形成并提供关键见解。我们发现，为了使两个人之间建立信任，需要满足一定程度的社会化门槛。此阈值因人而异，也取决于网络。一旦在通过某种社会关系连接的两个角色之间也建立了信任关系（也称为字符二元组），就可以以较低的社会化速率维持信任。我们的第一组实验是关系预测问题。通过查看网络的过去特征，我们可以预测一段时间内两个人之间的社会关系的出现，例如分组，指导和交易。我们发现与信任有关的功能对该预测影响很小。在最后一组实验中，我们通过查看个体之间的地形和语义社会互动特征来预测个体之间信任的形成。我们为该任务生成了三个语义维度，可以使用观察到的社交变量（例如分组）重新计算三个维度，以创建一个新的语义社交变量。在这项工作中，我们成功地表明，包括与社交相关的功能，可以使我们对信任关系预测的准确度大约提高4–9％。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号