Text mining of personal communication

This paper reports on the work on a new service using text mining on SMS data: SMSTrends. The service extracts trends in the form of keywords from SMS messages sent and received by ad hoc location-based communities of users. Trends are then presented to the user using a phone widget, which is regularly updated to show the latest trends. This allows the user to see what the user community is texting about, and makes her aware of what is going on in this community. Privacy considerations of the service are governed by user expectations and regulations. Brenner and Wang discussed mining of personal communication in operator bit pipes. We expand on this by looking deeper into privacy and regulatory aspects through the specific example of SMSTrends. Especially, the use of adaptive location granularity selection is introduced.