A study of retrospective and on-line event detection
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
The Journal of Machine Learning Research
A probabilistic approach to spatiotemporal theme pattern mining on weblogs
Proceedings of the 15th international conference on World Wide Web
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Emerging topic detection on Twitter based on temporal and social terms evaluation
Proceedings of the Tenth International Workshop on Multimedia Data Mining
A latent variable model for geographic lexical variation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Geographical topic discovery and comparison
Proceedings of the 20th international conference on World wide web
Finding hierarchy in directed online social networks
Proceedings of the 20th international conference on World wide web
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Multiscale Poisson Intensity and Density Estimation
IEEE Transactions on Information Theory
Towards context-aware search and analysis on social media data
Proceedings of the 16th International Conference on Extending Database Technology
A probablistic model for spatio-temporal signal extraction from social media
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Spatio-temporal characteristics of bursty words in Twitter streams
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Reliable spatio-temporal signal extraction and exploration from human activity records
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
Socioscope: spatio-temporal signal recovery from social media (extended abstract)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Many real-world phenomena can be represented by a spatio-temporal signal: where, when, and how much. Social media is a tantalizing data source for those who wish to monitor such signals. Unlike most prior work, we assume that the target phenomenon is known and we are given a method to count its occurrences in social media. However, counting is plagued by sample bias, incomplete data, and, paradoxically, data scarcity --- issues inadequately addressed by prior work. We formulate signal recovery as a Poisson point process estimation problem. We explicitly incorporate human population bias, time delays and spatial distortions, and spatio-temporal regularization into the model to address the noisy count issues. We present an efficient optimization algorithm and discuss its theoretical properties. We show that our model is more accurate than commonly-used baselines. Finally, we present a case study on wildlife roadkill monitoring, where our model produces qualitatively convincing results.