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How flickr helps us make sense of the world: context and content in community-contributed media collections (2007)
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| Venue: | In Proceedings of the 15th International Conference on Multimedia (MM2007 |
| Citations: | 103 - 5 self |
BibTeX
@INPROCEEDINGS{Naaman07howflickr,
author = {Mor Naaman and Shane Ahern and Rahul Nair and Tye Rattenbury},
title = {How flickr helps us make sense of the world: context and content in community-contributed media collections},
booktitle = {In Proceedings of the 15th International Conference on Multimedia (MM2007},
year = {2007},
pages = {631--640},
publisher = {ACM}
}
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Abstract
The advent of media-sharing sites like Flickr and YouTube has drastically increased the volume of community-contributed multimedia resources available on the web. These collections have a previously unimagined depth and breadth, and have generated new opportunities – and new challenges – to multimedia research. How do we analyze, understand and extract patterns from these new collections? How can we use these unstructured, unrestricted community contributions of media (and annotation) to generate “knowledge”? As a test case, we study Flickr – a popular photo sharing website. Flickr supports photo, time and location metadata, as well as a light-weight annotation model. We extract information from this dataset using two different approaches. First, we employ a location-driven approach to generate aggregate knowledge in the form of “representative tags ” for arbitrary areas in the world. Second, we use a tag-driven approach to automatically extract place and event semantics for Flickr tags, based on each tag’s metadata patterns. With the patterns we extract from tags and metadata, vision algorithms can be employed with greater precision. In particular, we demonstrate a location-tag-vision-based approach to retrieving images of geography-related landmarks and features from the Flickr dataset. The results suggest that community-contributed media and annotation can enhance and improve our access to multimedia resources – and our understanding of the world.
Keyphrases
community-contributed medium collection tag metadata pattern location-driven approach community-contributed multimedia resource light-weight annotation model different approach unimagined depth flickr dataset location metadata media-sharing site new collection extract pattern event semantics popular photo unrestricted community contribution representative tag new challenge geography-related landmark aggregate knowledge community-contributed medium vision algorithm arbitrary area tag-driven approach test case flickr tag location-tag-vision-based approach new opportunity
