Text classification and named entities for new event detection
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
YAGO2: exploring and querying world knowledge in time, space, context, and many languages
Proceedings of the 20th international conference companion on World wide web
Semantic enrichment of twitter posts for user profile construction on the social web
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Workshop on multimodal crowd sensing (CrowdSens 2012)
Proceedings of the 21st ACM international conference on Information and knowledge management
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Twitter is a popular tool for publishing potentially interesting information about people's opinions, experiences and news. Mobile devices allow people to publish tweets during real-time events. It is often difficult to identify the subject of a tweet because Twitter users often write using highly unstructured language with many typographical errors. Structured data related to entities can provide additional context to tweets. We propose an approach which associates tweets to a given event using query expansion and relationships defined on the Semantic Web, thus increasing the recall whilst maintaining or improving the precision of event detection. In this work, we investigate the usage of Twitter in discussing the Rock am Ring music festival. We aim to use prior knowledge of the festival's lineup to associate tweets with the bands playing at the festival. In order to evaluate the effectiveness of our approach, we compare the lifetime of the Twitter buzz surrounding an event to the actual programmed event, using Twitter users as social sensors.