Approximating multi-dimensional aggregate range queries over real attributes
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Sampling from a moving window over streaming data
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding how bloggers feel: recognizing affect in blog posts
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Tweet the debates: understanding community annotation of uncollected sources
WSM '09 Proceedings of the first SIGMM workshop on Social media
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Revising the wordnet domains hierarchy: semantics, coverage and balancing
MLR '04 Proceedings of the Workshop on Multilingual Linguistic Ressources
Learning similarity metrics for event identification in social media
Proceedings of the third ACM international conference on Web search and data mining
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
TwitterMonitor: trend detection over the twitter stream
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
A latent variable model for geographic lexical variation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Robust sentiment detection on Twitter from biased and noisy data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Event discovery in social media feeds
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Identifying content for planned events across social media sites
Proceedings of the fifth ACM international conference on Web search and data mining
Summarizing sporting events using twitter
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Discovering geographical topics in the twitter stream
Proceedings of the 21st international conference on World Wide Web
Effects of the recession on public mood in the UK
Proceedings of the 21st international conference companion on World Wide Web
See what's enBlogue: real-time emergent topic identification in social media
Proceedings of the 15th International Conference on Extending Database Technology
On the spatiotemporal burstiness of terms
Proceedings of the VLDB Endowment
Open domain event extraction from twitter
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Twevent: segment-based event detection from tweets
Proceedings of the 21st ACM international conference on Information and knowledge management
Limosa: a system for geographic user interest analysis in Twitter
Proceedings of the 16th International Conference on Extending Database Technology
Active Evaluation of Classifiers on Large Datasets
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
Location Extraction from Social Networks with Commodity Software and Online Data
ICDMW '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining Workshops
Hierarchical geographical modeling of user locations from social media posts
Proceedings of the 22nd international conference on World Wide Web
| Hi-index | 0.00 |
Microblogging platforms, such as Twitter, Tumblr etc., have been established as key components in the contemporary Web ecosystem. Users constantly post snippets of information regarding their actions, interests or perception of their surroundings, which is why they have been attributed the term Live Web. Nevertheless, research on such platforms has been quite limited when it comes to identifying events, but is rapidly gaining ground. Event identification is a key step to news reporting, proactive or reactive crisis management at multiple scales, efficient resource allocation, etc. In this paper, we focus on the problem of automatically identifying events as they occur, in such a user-driven, fast paced and voluminous setting. We propose a novel and natural way to address the issue using notions from emotional theories, combined with spatiotemporal information and employ online event detection mechanisms to solve it at large scale in a distributed fashion. We present a modular framework that incorporates all of our key ideas and experimentally validate its superiority, in terms of both efficiency and effectiveness, over the state-of-the-art using real life data from the Twitter stream. We also present empirical evidence on the importance of spatiotemporal information in event detection for this setting.