Graz University of Technology On the Navigability of Social Tagging On the Navigability of Social Tagging Systems Christoph Trattner Knowledge Management Institute and Institute for Information Systems and Computer Media Graz University of Technology, Austria e-mail: ctrattner@iicm.edu web: http://www.austria-lexikon.at/af/User/Trattner%20Christoph In collaboration with: D.Helic, M.Strohmaier, K. Andrews Christoph Trattner 2011 1
Graz University of Technology What is a tagging system and what are What is a tagging system and what are tags? What is a tagging system? A system that provides the user the possibility to A system that provides the user the possibility to apply tags to resources What are tags? g - lightweight keywords (free form vocabulary) - generated by users - for users Christoph Trattner 2011 2
3 Popular Examples Popular Examples 2011 Graz University of Technology Christoph Trattner
Graz University of Technology Why system designers like tags? - Tags add additional meta data to resources for which Tags add additional meta data to resources for which typically just sparse meta data information exists (such as pictures, movies, etc.) - Trough tags system designers are able to provide the user with simple navigational tools that improve the systems information retrieval properties - Tags are cheap!!! Christoph Trattner 2011 4
Graz University of Technology Why users like tags? - Trough tags users are able to categorize or describe Trough tags users are able to categorize or describe resources - Can find information faster - through personal tags - Can find related content faster - trough related tags Christoph Trattner 2011 5
Graz University of Technology Navigation with Tags Typically tagging systems provide the user the following forms of information retrieval interfaces to navigate content of a tagging system 1. Tag clouds – widely used 2 T 2. Tag hierarchies hi hi new – hardly any implementations yet Christoph Trattner 2011 Gupta et al. 2010 6
Graz University of Technology How does tag (cloud) based navigation How does tag (cloud) based navigation look like? Christoph Trattner 2011 7
Graz University of Technology Questions??? Are Tag Clouds useful for navigation? Christoph Trattner 2011 8
Graz University of Technology Modelling a tag dataset as a graph (1/2) - A tagging dataset is typically modeled as a tripartite A t i d t t i t i ll d l d t i tit hypergraph - V = R U U U T - An annotation is a hyperedge (r, t, u) - A tripartite hypergraph can be mapped onto three bipartite graphs connecting users and resources bipartite graphs connecting users and resources, users and tags, and tags and resources. Christoph Trattner 2011 9
Graz University of Technology Defining Navigability A network is navigable iff: There is a short path between all or almost all pairs of nodes in the network. d i th t k Formally: Formally: 1. There exists a giant component 2 2. The effective diameter is low (bounded by log n) The effective diameter is low (bounded by log n) J. Kleinberg. The small-world phenomenon: An algorithmic perspective. Proc. 32nd ACM Symposium on Theory of Computing, 2000. Also appears as Cornell Computer Science Technical Report 99-1776 (October 1999) Christoph Trattner 2011 10
Graz University of Technology Navigability: Examples Example 1: Not navigable : No giant component Example 2: Not navigable : Not navigable : giant component BUT giant component, BUT eff.diam: 7 > log 2 (8) Christoph Trattner 2011 11
Graz University of Technology Navigability: Examples Example 3: Navigable : Giant component AND eff diam: 2 < log (10) eff.diam: 2 < log 2 (10) Is this efficiently navigable? Is this efficiently navigable? There are short paths between all nodes, but can an agent or algorithm find them with local knowledge only ? Christoph Trattner 2011 12
Graz University of Technology Efficiently navigable A network is efficiently navigable iff: If there is an algorithm that can find a short path with only local knowledge, and the delivery time of the l l l k l d d th d li ti f th algorithm is bounded polynomially by log k (n). Example 4: B A C Efficiently navigable, if the algorithm knows it needs to go through A � B � C J. Kleinberg. The small-world phenomenon: An algorithmic perspective. Proc. 32nd ACM Symposium on Theory of Computing, 2000. Also appears as Cornell Computer Science Technical Report 99-1776 (October 1999) Christoph Trattner 2011 13
Graz University of Technology Navigability of Social Tagging Systems (1/2) Christoph Trattner 2011 14
Graz University of Technology Navigability of Social Tagging Systems (2/2) . „Hub“ tags Tagging networks are navigable power-law networks. For power law networks, efficient sub-linear decentralised navigation algorithms exist. t k ffi i t b li d t li d i ti l ith i t Christoph Trattner 2011 15
Graz University of Technology But how about User Interface constraints? Tag Cloud Size n topN resources (topN most common algorithm) Pagination of resources / tag k resources shown / page k resources shown / page (reverse chronological ordering) Christoph Trattner 2011 16
Graz University of Technology How UI constraints effect Navigability Tag Cloud Size . Pagination Limiting the tag cloud size n to practically feasible sizes (e.g. 5, 10, or more) does not influence navigability (this is not very surprising). BUT : Limiting the out-degree of high frequency tags k (e.g. through pagination with resources sorted in reverse-chronological order) leaves the network vulnerable to fragmentation. This destroys navigability of prevalent approaches vulnerable to fragmentation. This destroys navigability of prevalent approaches to tag clouds. Christoph Trattner 2011 17
Graz University of Technology Questions??? How can we recover the navigability of social tagging systems? Answer: Through resource specific resource list construction! construction! Christoph Trattner 2011 18
Graz University of Technology What is a resource specific resource list ? • A A resource specific resource list is a resource list ifi li t i li t that is not only specific to a particular tag but also to a particular resource in the tagging also to a particular resource in the tagging system • Typically resource lists are calculated as follows Res(t) = {r i (t) Res(t) {r i (t),…,r n (t)} r n (t)} • Resource specific resource lists are calculated as as Res(t,r) = {r i (t,r),…,r n (t,r)} Christoph Trattner 2011 19
Graz University of Technology Approach: Random Ordering -Instead of reverse-chronological ordering of resources, we apply a random ordering. - On each click on a particular tag a different resource list is generated - Problem: network is not efficiently navigable Better algorithms can easily be envisioned. Christoph Trattner 2011 20
Graz University of Technology Approach: Hierarchical Ordering • Instead of random ordering, we use hierarchical background knowledge for ranking paginated reso rces [Kleinberg 2001] resources [Kleinberg 2001]. • Kleinberg showed that if the nodes of a network can be organized into a hierarchy then such a can be organized into a hierarchy, then such a hierarchy provides a probability distribution for connecting the nodes in the network. g • For such a network a hierarchical decentralized searcher exists that is able to navigate the network in log(n) => the network is efficiently navigable J. M. Kleinberg, “Small-world phenomena and the dynamics of information,” in Advances in Neural Information Processing Systems (NIPS), 14. MIT Press, 2001, p. 2001. Christoph Trattner 2011 21
Graz University of Technology Approach: Hierarchical Ordering J. M. Kleinberg, “Small-world phenomena and the dynamics of information,” in Advances in Neural Information Processing Systems (NIPS), 14. MIT Press, 2001, p. 2001. Christoph Trattner 2011 22
Graz University of Technology Problem: Semantic Penalty • Hierarchy was more or less randomly constructed • Does not take semantic similarity between resources into account • H Hence, two new approaches were developed t h d l d • First idea, constructing efficiently navigable tag clouds from structured web content [Trattner 2011] from structured web content [Trattner 2011] • Second idea, develop an algorithm that is able to construct semantically correct resource hierarchies from tagging data [Trattner 2011a] from tagging data [Trattner 2011a] C. Trattner , D. Helic, M. Strohmaier, “On the Construction of Efficiently Navigable Tag Clouds Using Knowledge from Structured Web Content,” in JUCS, Volume 17, Issue 4, 565-582, 2011. C. Trattner , “Improving the Navigability of Tagging Systems with Hierarchically Constructed Resource Lists and Tag Trails” submitted to a journal, 2011. p g g y gg g y y g j Christoph Trattner 2011 23
Graz University of Technology O On the construction of efficiently navigable tag th t ti f ffi i tl i bl t clouds from structured web content • Content on the Web not always flat • There are websites that provide a hierarchical structure • Example: Austria-Forum Christoph Trattner 2011 24
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