Mining E-Mail Messages: Uncovering Interaction Patterns and Processes Using E-Mail Logs

Abstract

Increasingly information systems log historic information in a systematic way. Workflow management systems, but also ERP, CRM, SCM, and B2B systems often provide a so-called “event log’’, i.e., a log recording the execution of activities. Thus far, process mining has been mainly focusing on structured event logs resulting in powerful analysis techniques and tools for discovering process, control, data, organizational, and social structures from event logs. Unfortunately, many work processes are not supported by systems providing structured logs. Instead very basic tools such as text editors, spreadsheets, and e-mail are used. This paper explores the application of process mining to e-mail, i.e., unstructured or semi-structured e-mail messages are converted into event logs suitable for application of process mining tools. This paper presents the tool EMailAnalyzer, embedded in the ProM process mining framework, which analyzes and transforms e-mail messages to a format that allows for analysis using our process mining techniques. The main innovative aspect of this work is that, unlike most other work in this area, our analysis is not restricted to social network analysis. Based on e-mail logs we can also discover interaction patterns and processes.