Visualizing tags over time

Abstract

We consider the problem of visualizing the evolution of tags within the Flickr (flickr.com) online image sharing community. 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. Understanding 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 support the efficient generation of this visualization. We combine 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.

Mining discriminative items in multiple data streams

“…Our problem of finding discriminative items between two streams can provide solutions to many Web mining applications such as tag suggestions [22,28,42,53] summarizing web documents [40,59], emails [10], or Web search results [32], search engine query analysis [56], social network analysis [49,54], and so on. An essential issue inherent in those applications is to find discriminative tags or keywords that can distinguish the targeting object from many others.…”

Visualization of Heterogeneous Data

“…The visualization of unstructured data, such as documents, webpages, and tags, is studied in several papers [14,17,13,15]. For structured data, Catarci et al [12] surveyed a large number of systems that visualize relational data.…”

Automatic Web Tagging and Person Tagging Using Language Models

“…The same ranking function can be used to generate labels for this user language model, by replacing p(w|d) with p(w|u) in Equation 4. Similarly, by taking time into consideration, one can also suggest tags for a web document in different time periods, by replacing p(w|d) with p(w|d, time).…”

“…Recently, researchers have started to realize the importance of social bookmarking. This leads to the exploration of tagging logs in different ways [5,10,4,8,7,15]. Most work are focusing on utilizing social tags, instead of suggesting tags.…”

“…Most work are focusing on utilizing social tags, instead of suggesting tags. Folksonomy [10], tagging visualization [4], and spam detection for tagging system [8] are some of such examples. [2] utilizes social tags to help summarization.…”