In recent years, examination of the social media networks has become an integral part of investigations. Law enforcement agencies and legal practitioners frequently utilize social networks to quickly access the information related to the participants of any illicit incident. However, the forensic process needs collection and analysis of the information which is immense, heterogeneous, and spread across multiple social networks. This process is technically intricate due to heterogeneous and unstructured online social networks (OSNs). Hence, creating cognitive challenges and massive workloads for the investigators. Therefore, it is imperative to develop automated and reliable solutions to assist investigators. Capturing the forensic information in the structured form is crucial for automation, sharing, and interoperability. This paper introduces the design of a multi-layer framework; from collection to evidence analysis. The central component of this framework is a hybrid ontology approach that involves multiple ontologies to manage the unstructured data and integrate various social media data collections. This approach aims to find the evidence by automated methods that are trustworthy and therefore admissible in a court of law.

近年来，对社交媒体网络的检查已成为调查的组成部分。执法机构和法律从业人员经常利用社交网络快速访问与任何非法事件参与者有关的信息。但是，取证过程需要收集和分析巨大，异构且分布在多个社交网络中的信息。由于异构和非结构化的在线社交网络（OSN），此过程在技术上很复杂。因此，给研究人员带来认知挑战和繁重的工作量。因此，必须开发自动化和可靠的解决方案来协助调查人员。以结构化形式捕获取证信息对于自动化，共享和互操作性至关重要。本文介绍了一个多层框架的设计。从收集到证据分析。该框架的核心组件是一种混合本体方法，它涉及多个本体来管理非结构化数据并集成各种社交媒体数据集合。这种方法旨在通过可信赖的自动方法来查找证据，因此可以在法院接受。