Many existing location sharing applications provide coordinate-based location estimates and display them on a map. However, people use a rich variety of terms to convey their location to others, such as "home," "Starbucks," or even "the bus stop near my apartment." Our long-term goal is to create a system that can automatically generate useful place names based on real-time context. Towards this end, we present the results of a week-long study with 30 participants to understand people's preferences for place naming. We propose a hierarchical classification on place naming methods. We further conclude that people's place naming preferences are complex and dynamic, but fairly predictable using machine learning techniques. Two factors influence the way people name a place: their routines and their willingness to share location information. The new findings provide important implications to location sharing applications and other location based services.

24 pages