The Journal of Machine Learning Research
Adaptive event detection with time-varying poisson processes
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Planetary-scale views on a large instant-messaging network
Proceedings of the 17th international conference on World Wide Web
PET: a statistical model for popular events tracking in social communities
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Measuring geographical regularities of crowd behaviors for Twitter-based geo-social event detection
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
Exploratory novelty identification in human activity data streams
Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming
Tracking trends: incorporating term volume into temporal topic models
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Visual analysis of microblog content using time-varying co-occurrence highlighting in tag clouds
Proceedings of the International Working Conference on Advanced Visual Interfaces
Discovering regions of different functions in a city using human mobility and POIs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
City-scale traffic simulation from digital footprints
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
When a city tells a story: urban topic analysis
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
A novel method for geographical social event detection in social media
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Prediction of user location using the radiation model and social check-ins
Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing
Temporal decomposition and semantic enrichment of mobility flows
Proceedings of the 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks
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Human-generated textual data streams from services such as Twitter increasingly become geo-referenced. The spatial resolution of their coverage improves quickly, making them a promising instrument for sensing various aspects of evolution and dynamics of social systems. This work explores spacetime structures of the topical content of short textual messages in a stream available from Twitter in Ireland. It uses a streaming Latent Dirichlet Allocation topic model trained with an incremental variational Bayes method. The posterior probabilities of the discovered topics are post-processed with a spatial kernel density and subjected to comparative analysis. The identified prevailing topics are often found to be spatially contiguous. We apply Markov-modulated non-homogeneous Poisson processes to quantify a proportion of novelty in the observed abnormal patterns. A combined use of these techniques allows for real-time analysis of the temporal evolution and spatial variability of population's response to various stimuli such as large scale sportive, political or cultural events.