Towards situational pattern mining from microblogging activity.

Many useful patterns can be derived from analyzing microblogging behavior at different scales (individual and social group). In this paper, we derive patterns relating to spatio-temporal traffic flow, visit regularity, content and social ties as they relate to an individual's activities in an urban environment (e.g., New York City). We also demonstrate, through an example, methods for reasoning about the activities, locations and group structures that may underlie the microblogging messages in the aforementioned context of mining situation patterns. These individual and group situational patterns may be very crucial when planning for disruptions and organized response.