@inproceedings{kennedy2007how,
  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.},
  address = {New York, NY, USA},
  author = {Kennedy, Lyndon and Naaman, Mor and Ahern, Shane and Nair, Rahul and Rattenbury, Tye},
  booktitle = {MULTIMEDIA '07: Proceedings of the 15th international conference on Multimedia},
  citeulike-article-id = {2626639},
  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1291384},
  citeulike-linkout-1 = {http://dx.doi.org/10.1145/1291233.1291384},
  doi = {10.1145/1291233.1291384},
  file = {kennedy2007how.pdf:kennedy2007how.pdf:PDF},
  groups = {public},
  interhash = {cd4acdd5a627c20e9effdbda54dd122d},
  intrahash = {7069480c43ba5d41396e075307cd1af1},
  isbn = {9781595937025},
  pages = {631--640},
  posted-at = {2009-06-25 14:41:53},
  priority = {2},
  publisher = {ACM},
  timestamp = {2011-02-17 11:07:22},
  title = {How flickr helps us make sense of the world: context and content in community-contributed media collections},
  url = {http://dx.doi.org/10.1145/1291233.1291384},
  username = {dbenz},
  year = 2007
}

@inproceedings{capocci2010friendship,
  abstract = {We study the semantic assortativity in the social networks hosted by the Flickr folksonomy, based both on the contact data and on the group membership data provided by the users. The social network built this way are complex one. Besides, one observes a clear assortativity pattern, stronger than in a suitable null model adopted for a comparison. Nevertheless, such semantical similarity does not appear to develop during the community evolution, but is rather the result of a pre-existing shared background between users.},
  address = {New York, NY, USA},
  author = {Capocci, Andrea and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio},
  booktitle = {MSM '10: Proceedings of the International Workshop on Modeling Social Media},
  doi = {10.1145/1835980.1835988},
  interhash = {ee0aa2dc8267b105f9491e04f5edcee2},
  intrahash = {de0827988d3609f2ac66bd90f12ac93a},
  isbn = {978-1-4503-0229-6},
  location = {Toronto, Ontario, Canada},
  pages = {1--4},
  publisher = {ACM},
  title = {Friendship, collaboration and semantics in Flickr: from social interaction to semantic similarity},
  url = {http://portal.acm.org/citation.cfm?id=1835980.1835988},
  year = 2010
}

@inproceedings{wu2008flickr,
  address = {New York, NY, USA},
  author = {Wu, Lei and Hua, Xian-Sheng and Yu, Nenghai and Ma, Wei-Ying and Li, Shipeng},
  booktitle = {MM '08: Proceeding of the 16th ACM international conference on Multimedia},
  doi = {http://doi.acm.org/10.1145/1459359.1459364},
  interhash = {7aeae0773262c83a7efd2f0757ec5290},
  intrahash = {f8f536ebee1f06fd53bc8b28f7f124c0},
  isbn = {978-1-60558-303-7},
  location = {Vancouver, British Columbia, Canada},
  pages = {31--40},
  publisher = {ACM},
  title = {Flickr distance},
  url = {http://portal.acm.org/citation.cfm?doid=1459359.1459364},
  year = 2008
}

@article{tonkin2006folksonomies,
  abstract = {A folksonomy is a type of distributed classification system. It is usually created by a group of individuals, typically the resource users. Users add tags to online items, such as images, videos, bookmarks and text. These tags are then shared and sometimes refined. In this article we look at what makes folksonomies work. We agree with the premise that tags are no replacement for formal systems, but we see this as being the core quality that makes folksonomy tagging so useful.},
  author = {Tonkin, Emma and Guy, Marieke},
  file = {tonkin2006folksonomies.pdf:tonkin2006folksonomies.pdf:PDF},
  interhash = {535e0aea1bcbd7feb85a7495f284a589},
  intrahash = {f56571b67b4e70a7d108dc8529d4c937},
  journal = {D-Lib},
  lastdatemodified = {2006-07-18},
  lastname = {Tonkin},
  location = {San Diego, California},
  month = {January},
  number = 1,
  own = {own},
  pdf = {tonkin06-folksonomies.pdf},
  read = {read},
  title = {Folksonomies: Tidying Up Tags?},
  url = {http://www.cs.bris.ac.uk/Publications/pub_info.jsp?id=2000478},
  volume = 12,
  year = 2006
}

@inproceedings{schmitz2006inducing,
  address = {Edinburgh, Scotland},
  author = {Schmitz, Patrick},
  booktitle = {Collaborative Web Tagging Workshop at WWW 2006},
  file = {schmitz2006inducing.pdf:schmitz2006inducing.pdf:PDF},
  interhash = {1335f4ef87f951e6edf4fd94f885d3a2},
  intrahash = {5a9065e96237a69d95edebc03ccac92d},
  month = may,
  pdf = {schmitz2006inducing.pdf},
  title = {Inducing Ontology from Flickr Tags.},
  year = 2006
}

@inproceedings{marlow2006position,
  abstract = {In recent years, tagging systems have become increasingly popular. These systems enable users to add keywords (i.e., �tags�) to Internet resources (e.g., web pages, images, videos) without relying on a controlled vocabulary. Tagging systems have the potential to improve search, spam detection, reputation systems, and personal organization while introducing new modalities of social communication and opportunities for data mining. This potential is largely due to the social structure that underlies many of the current systems. Despite the rapid expansion of applications that support tagging of resources, tagging systems are still not well studied or understood. In this paper, we provide a short description of the academic related work to date. We offer a model of tagging systems, specifically in the context of web-based systems, to help us illustrate the possible benefits of these tools. Since many such systems already exist, we provide a taxonomy of tagging systems to help inform their analysis and design, and thus enable researchers to frame and compare evidence for the sustainability of such systems. We also provide a simple taxonomy of incentives and contribution models to inform potential evaluative frameworks. While this work does not present comprehensive empirical results, we present a preliminary study of the photosharing and tagging system Flickr to demonstrate our model and explore some of the issues in one sample system. This analysis helps us outline and motivate possible future directions of research in tagging systems.},
  address = {Edinburgh, Scotland},
  author = {Marlow, Cameron and Naaman, Mor and Boyd, Danah and Davis, Marc},
  booktitle = {Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006},
  file = {marlow2006position.pdf:marlow2006position.pdf:PDF},
  groups = {public},
  interhash = {7446351e0d902ee4f36fb750f82c50a5},
  intrahash = {d9f433de0945351fa2157c1424d9fe67},
  lastdatemodified = {2006-07-17},
  lastname = {Marlow},
  month = May,
  own = {own},
  pdf = {marlow06-tagging.pdf},
  read = {readnext},
  timestamp = {2007-09-11 13:31:31},
  title = {{Position Paper, Tagging, Taxonomy, Flickr, Article, ToRead}},
  url = {http://.rawsugar.com/www2006/cfp.html},
  username = {dbenz},
  year = 2006
}

@inproceedings{rattenbury2007towards,
  abstract = {We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr, a popular photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns.},
  address = {New York, NY, USA},
  author = {Rattenbury, Tye and Good, Nathaniel and Naaman, Mor},
  booktitle = {SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
  doi = {10.1145/1277741.1277762},
  file = {rattenbury2007towards.pdf:rattenbury2007towards.pdf:PDF},
  groups = {public},
  interhash = {8b02d2b3fdbb97c3db6e3b23079a56e5},
  intrahash = {bf6f73d2ef74ca6f1d355fb5688b673c},
  isbn = {978-1-59593-597-7},
  pages = {103--110},
  publisher = {ACM Press},
  timestamp = {2010-11-10 15:35:25},
  title = {Towards automatic extraction of event and place semantics from flickr tags},
  url = {http://dx.doi.org/10.1145/1277741.1277762},
  username = {dbenz},
  year = 2007
}

@inproceedings{plangprasopchok2010growing,
  abstract = {Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured metadata provide valuable evidence for learning how a com- munity organizes knowledge. For instance, we can aggre- gate many personal hierarchies into a common taxonomy, also known as a folksonomy, that will aid users in visualiz- ing and browsing social content, and also to help them in organizing their own content. However, learning from social metadata presents several challenges, since it is sparse, shal- low, ambiguous, noisy, and inconsistent. We describe an ap- proach to folksonomy learning based on relational clustering, which exploits structured metadata contained in personal hierarchies. Our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. We study folksonomy learning using social metadata extracted from the photo- sharing site Flickr, and demonstrate that the proposed ap- proach addresses the challenges. Moreover, comparing to previous work, the approach produces larger, more accurate folksonomies, and in addition, scales better.},
  author = {Plangprasopchok, Anon and Lerman, Kristina and Getoor, Lise},
  booktitle = {KDD},
  crossref = {conf/kdd/2010},
  editor = {Rao, Bharat and Krishnapuram, Balaji and Tomkins, Andrew and Yang, Qiang},
  ee = {http://doi.acm.org/10.1145/1835804.1835924},
  file = {plangprasopchok2010growing.pdf:plangprasopchok2010growing.pdf:PDF},
  groups = {public},
  interhash = {d8738d21c4d25559d7dbcc0aa6647223},
  intrahash = {11fbd76695bf0de7499c1721723661fe},
  isbn = {978-1-4503-0055-1},
  pages = {949-958},
  publisher = {ACM},
  timestamp = {2011-02-02 15:03:59},
  title = {Growing a tree in the forest: constructing folksonomies by integrating structured metadata.},
  url = {http://dblp.uni-trier.de/db/conf/kdd/kdd2010.html#PlangprasopchokLG10},
  username = {dbenz},
  year = 2010
}