In recent years, complex networks have been used as new tools to study patterns in earthquake data. Although various methods have been developed to construct earthquake networks, there is still a long way to use this approach as a complete framework for analyzing seismicity. This research develops novel methods for building earthquake networks and investigates the patterns that they could reveal. The proposed methods use a specific declustered catalog and define nodes based on main shocks and edges on aftershocks’ period or sequence. Another method is offered to convert the resulted networks, as earthquake networks, to epicenters networks. The catalog of Iran’s earthquakes from 2006 to 2018 is used to produce earthquake networks using the above-mentioned methods. The resulted networks are scale-free and hierarchical with community structure, as expected. Some nodes’ features in the networks are shown correlated with the magnitude of the related event. Most patterns and features are preserved while converting the earthquakes network to epicenters network. Proposed methods better capture a region’s seismic features into a complex network with a more precise relationship between seismological laws and network characteristics and can help develop perfect seismicity analyzing framework based on complex networks.

近年来，复杂的网络已被用作研究地震数据模式的新工具。尽管已经开发了各种方法来构造地震网络，但是使用这种方法作为分析地震活动性的完整框架还有很长的路要走。这项研究开发了用于构造地震网络的新颖方法，并研究了它们可能揭示的模式。所提出的方法使用特定的分簇目录，并根据余震周期或序列上的主要冲击和边缘来定义节点。提供了另一种方法来将生成的网络（如地震网络）转换为震中网络。使用上述方法，将2006年至2018年的伊朗地震目录用于产生地震网络。产生的网络是无规模的，具有社区结构的分层结构，如预期的那样。显示了网络中某些节点的特征与相关事件的大小相关。在将地震网络转换为震中网络时，大多数模式和特征都得以保留。提出的方法可以更好地将区域的地震特征捕获到复杂的网络中，并在地震定律和网络特征之间建立更精确的关系，并且可以帮助开发基于复杂网络的完善的地震活动性分析框架。