Spranger, MichaelXi, JianJaeckel, LukasFelser, JennyLabudde, Dirk2023-01-182023-01-1820222022http://dx.doi.org/10.1007/s13218-022-00762-whttps://dl.gi.de/handle/20.500.12116/40042Mobile communication devices are a popular means of planning, commissioning and carrying out criminal offenses. In particular, data from messengers such as WhatsApp or Telegram often contain conclusive information. Organized crime also usually involves many devices, but not all of them contain the full history of communication. Rather, it is heavily fragmented due to individual deletions of messages or different joining times to groups. A singular evaluation of individual devices is therefore often not expedient, since important relationships cannot be recognized. Furthermore, communication is often distributed across different channels and modalities and can only be fully and correctly understood through a joint semantic analysis. The linking of related communications of different devices enables an almost complete reconstruction of the communication with a simultaneous reduction in reading effort by merging identical messages. Grouping coherent messages into conversations enables efficient comparison with a knowledge model. Building such a model is complex, but can be supported by a term recommender system. In this paper, MoNA is presented as a platform that implements these approaches and enables an assisted analysis of mobile communications.Digital forensicsExpert systemMobile communicationText/Journal Article10.1007/s13218-022-00762-w1610-1987