We consider the problem of visualizing the evolution of tags within
the Flickr (flickr.com) online image sharing com- munity. Any user
of the Flickr service may append a tag to any photo in the system.
Over the past year, users have on average added over a million tags
each week. Under- standing the evolution of these tags over time
is therefore a challenging task. We present a new approach based
on a characterization of the most interesting tags associated with
a sliding interval of time. An animation provided via Flash in a
web browser allows the user to observe and interact with the interesting
tags as they evolve over time. New algorithms and data structures
are required to sup- port the efficient generation of this visualization.
We com- bine a novel solution to an interval covering problem with
extensions to previous work on score aggregation in order to create
an efficient backend system capable of producing visualizations at
arbitrary scales on this large dataset in real time.
%0 Conference Paper
%1 Dubinko_et_al_2006
%A Dubinko, Micah
%A Kumar, Ravi
%A Magnani, Joseph
%A Novak, Jasmine
%A Raghavan, Prabhakar
%A Tomkins, Andrew
%B Proceedings of the 15th international conference on World Wide Web(WWW
'06)
%C New York, NY, USA
%D 2006
%I ACM
%K Flickr Social_media Temporal_evolution Visualization
%P 193--202
%T Visualizing Tags over Time
%U http://portal.acm.org/citation.cfm?id=1135810
%X We consider the problem of visualizing the evolution of tags within
the Flickr (flickr.com) online image sharing com- munity. Any user
of the Flickr service may append a tag to any photo in the system.
Over the past year, users have on average added over a million tags
each week. Under- standing the evolution of these tags over time
is therefore a challenging task. We present a new approach based
on a characterization of the most interesting tags associated with
a sliding interval of time. An animation provided via Flash in a
web browser allows the user to observe and interact with the interesting
tags as they evolve over time. New algorithms and data structures
are required to sup- port the efficient generation of this visualization.
We com- bine a novel solution to an interval covering problem with
extensions to previous work on score aggregation in order to create
an efficient backend system capable of producing visualizations at
arbitrary scales on this large dataset in real time.
%@ 1-59593-323-9
@inproceedings{Dubinko_et_al_2006,
abstract = {We consider the problem of visualizing the evolution of tags within
the Flickr (flickr.com) online image sharing com- munity. Any user
of the Flickr service may append a tag to any photo in the system.
Over the past year, users have on average added over a million tags
each week. Under- standing the evolution of these tags over time
is therefore a challenging task. We present a new approach based
on a characterization of the most interesting tags associated with
a sliding interval of time. An animation provided via Flash in a
web browser allows the user to observe and interact with the interesting
tags as they evolve over time. New algorithms and data structures
are required to sup- port the efficient generation of this visualization.
We com- bine a novel solution to an interval covering problem with
extensions to previous work on score aggregation in order to create
an efficient backend system capable of producing visualizations at
arbitrary scales on this large dataset in real time.},
added-at = {2011-06-10T09:04:03.000+0200},
address = {New York, NY, USA},
author = {Dubinko, Micah and Kumar, Ravi and Magnani, Joseph and Novak, Jasmine and Raghavan, Prabhakar and Tomkins, Andrew},
biburl = {https://www.bibsonomy.org/bibtex/25828622f8982f37a522527ce9f4fe53e/bluedolphin},
booktitle = {Proceedings of the 15th international conference on World Wide Web(WWW
'06)},
ee = {http://doi.acm.org/10.1145/1135777.1135810},
interhash = {b9ff2f72831a1406013a86c8202d6276},
intrahash = {5828622f8982f37a522527ce9f4fe53e},
isbn = {1-59593-323-9},
keywords = {Flickr Social_media Temporal_evolution Visualization},
owner = {braun},
pages = {193--202},
publisher = {ACM},
timestamp = {2011-06-10T09:04:13.000+0200},
title = {Visualizing Tags over Time},
url = {http://portal.acm.org/citation.cfm?id=1135810},
year = 2006
}