ABSTRACT
There is an explosion of community-generated multimedia content available online. In particular, Flickr constitutes a 200-million photo sharing system where users participate following a variety of social motivations and themes. Flickr groups are increasingly used to facilitate the explicit definition of communities sharing common interests, which translates into large amounts of content (e.g. pictures and associated tags) about specific subjects. However, to our knowledge, an in-depth analysis of user behavior in Flickr groups remains open, as does the existence of effective tools to find relevant groups. Using a sample of about 7 million user-photos and about 51000 Flickr groups, we present a novel statistical group analysis that highlights relevant patterns of photo-to-group sharing practices. Furthermore, we propose a novel topic-based representation model for groups, computed from aggregated group tags. Groups are represented as multinomial distributions over semantically meaningful latent topics learned via unsupervised probabilistic topic modeling. We show this representation to be useful for automatically discovering groups of groups and topic expert-groups, for designing new group-search strategies, and for obtaining new insights of the semantic structure of Flickr groups.
- Flickr Blog, Jan. 2008. http://flickr.com/blog.Google Scholar
- S. Ahern, D. Eckles, N. S. Good, S. King, M. Naaman, and R. Nair. Over-exposed?: privacy patterns and considerations in online and mobile photo sharing. In CHI '07: Proceedings of the SIGCHI conference on Human factors in computing systems, 2007. Google ScholarDigital Library
- S. Ahern, M. Naaman, R. Nair, and J. H.-I. Yang. World explorer: visualizing aggregate data from unstructured text in geo-referenced collections. In JCDL '07: Proceedings of the 2007 conference on Digital libraries, 2007. Google ScholarDigital Library
- M. Ames and M. Naaman. Why we tag: motivations for annotation in mobile and online media. In CHI '07: Proceedings of the SIGCHI conference on Human factors in computing systems, 2007. Google ScholarDigital Library
- T. L. Berg and D. Forsyth. Automatic Ranking of Iconic Images. Technical report, U.C.Berkeley, 2007.Google Scholar
- M. Dubinko, R. Kumar, J. Magnani, J. Novak, P. Raghavan, and A. Tomkins. Visualizing tags over time. In WWW '06: Proceedings of the 15th international conference on World Wide Web, New York, NY, USA, 2006. Google ScholarDigital Library
- T. Hofmann. Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn., 42(1-2):177--196, 2001. Google ScholarDigital Library
- A. Jaffe, M. Naaman, T. Tassa, and M. Davis. Generating summaries for large collections of geo-referenced photographs. In Proceedings of the Fifteenth International World-Wide Web, Edinburgh, Scotland, 2006. Google ScholarDigital Library
- L. Kennedy, M. Naaman, S. Ahern, R. Nair, and T. Rattenbury. How Flickr Helps us Make Sense of the World: Context and Content in Community-Contributed Media Collections. Proc. ACM Multimedia, 2007. Google ScholarDigital Library
- R. Kumar, J. Novak, and A. Tomkins. Structure and evolution of online social networks. In KDD '06: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, 2006. Google ScholarDigital Library
- K. Lerman and L. Jones. Social Browsing on Flickr, Dec 2006.Google Scholar
- K. Lerman, A. Plangprasopchok, and C. Wong. Personalizing Image Search Results on Flickr, Apr 2007.Google Scholar
- R. Lienhart and M. Slaney. PLSA on Large Scale Image Databases. In Proceedings of the 2007 International Conference on Acoustics, Speech and Signal Processing, Honolulu, Hawaii, 2007.Google ScholarCross Ref
- C. Marlow, M. Naaman, D. Boyd, and M. Davis. HT06, tagging paper, taxonomy, flickr, academic article, to read. In HYPERTEXT '06: Proceedings of the seventeenth conference on Hypertext and hypermedia, 2006. Google ScholarDigital Library
- A. D. Miller and W. K. Edwards. Give and take: a study of consumer photo-sharing culture and practice. In CHI '07: Proceedings of the SIGCHI conference on Human factors in computing systems, 2007. Google ScholarDigital Library
- J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman. Object retrieval with large vocabularies and fast spatial matching. In IEEE Conference on Computer Vision and Pattern Recognition, 2007.Google ScholarCross Ref
- J. P. Pickett, editor. The American Heritage Dictionary of the English Language. Houghton Mifflin, January 2000.Google Scholar
- T. Rattenbury, N. Good, and M. Naaman. Towards Automatic Extraction of Event and Place Semantics from Flickr Tags. In SIGIR'07, 2007. Google ScholarDigital Library
- P. Schmitz. Inducing Ontology from Flickr Tags. In WWW 2006. IW3C2, 2006.Google Scholar
- P. Schmitz. Leveraging community annotations for image adaptation to small presentation formats. In MULTIMEDIA '06: Proceedings of the 14th annual ACM international conference on Multimedia, 2006. Google ScholarDigital Library
- N. A. Van House. Flickr and public image-sharing: distant closeness and photo exhibition. In CHI '07 extended abstracts on Human factors in computing systems, 2007. Google ScholarDigital Library
- R. van Zwol. Flickr: Who is Looking. In ACM International Conference on Web Intelligence (WI 2007), 2007. Google ScholarDigital Library
Index Terms
- Analyzing Flickr groups
Recommendations
Mining Tags from Flickr User Comments Using a Hybrid Ranking Model
ICSS '15: Proceedings of the 2015 International Conference on Service ScienceIn the Web2.0 era, user generated content has become the main source of information of many popular websites such as Flickr. In Flickr, each user can share his/her photos and browse others' easily. Tagging system is an important approach to the photo ...
Developing metrics to characterize Flickr groups
Flickr, the large-scale online photo sharing website, is often viewed as one of the ‘classic’ examples of Web2.0 applications through which researchers are able to observe the social behavior of online communities. One of the main features of Flickr is ...
Extracting Representative Tags for Flickr Users
ICDMW '10: Proceedings of the 2010 IEEE International Conference on Data Mining WorkshopsTags are very popular in online social communities (like You tube, Flickr) and provide valuable and crucial information for these communities. But at the same time, there exist a lot of noisy tags, which leads many researches to tag suggestion, tag ...
Comments