The interconnection network (ICN) is a vital component of a parallel machine and is often the limiting factor in the performance of several parallel applications. While ICN performance evaluation has been a widely researched topic, there have been very few studies that have used real applications to drive this research. In this paper we develop a framework for characterizing the communication properties of parallel applications. Message generation frequency, spatial distribution of messages and message length are the three attributes that quantify any communication. We develop a methodology to quantify these attributes, in particular the first two attributes. We employ two strategies, namely dynamic and static, in our methodology. In the former, the applications are executed on an execution-driven simulator called SPASM, while in the latter they are executed on a parallel machine, IBM SP2. We gather communication events from these executions and feed them to a 2-D mesh network simulator. The log of the network activity is then analyzed using a statistical analysis package (SAS) to find the message inter-arrival time distribution and spatial distribution via regression analysis. Five shared memory applications and two message passing applications are analyzed to quantify their communication workloads. It is shown that it is possible to express the message generation and spatial distribution of an application in terms of commonly used distributions. These distributions can be used in the analysis of ICNs for developing realistic performance models.