Event Identification in Social Media
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Hila Becker, Mor Naaman, Luis Gravano , "Event Identification in Social Media", in Proceedings of the ACM SIGMOD Workshop on the Web and Databases (WebDB '09), 2009.
![Social Media Sites Host Many “Event” Documents Photo-sharing: Flickr Video-sharing: YouTube Social networking: Facebook ,[object Object],[object Object],[object Object],[object Object],Social media documents for “All Points West” festival, Liberty State Park, New Jersey, 8/8/08](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Event Identification in Social Media
- 1. EVENT IDENTIFICATION IN SOCIAL MEDIA Hila Becker, Luis Gravano Mor Naaman Columbia University Rutgers University
- 6. Social Media Document Representation Title Description Tags Date/Time Location All-Text
- 8. Social Media Document Clustering Framework Document feature representation Social media documents Event clusters
- 9. Clustering: Ensemble Algorithm Consensus Function: combine ensemble similarities W title W tags W time f(C,W) C title C tags C time Ensemble clustering solution Learned in a training step
Editor's Notes
- Social media sites host a variety of event information We use the traditional event definition from the event detection literature, stating that an event is…, In particular, we consider events that range from …
- Our goal is to… This could facilitate application such as… as can be seen in this image, similar to news aggregation sites but for events, including a variety of rich media content Our approach for even identification uses clustering to group similar event documents, such that…
- Social media data quality is uneven When developing our approach, we had to consider the scalability of our algorithms as there exists a vast amount of social media event data on the web
- Define and motivate the event identification task…
- We have different notions of similarity for different types of features… We have to come up with a principled way to combine these different notions into a single similarity
- We can cluster out document collection according to the variety of feature reps. discussed, each would have its own
- Mention briefly where the event IDs came from…
- I’ll add a note on where these experiments stand
- Backup slide