FaceTag at IASummit 2007

FaceTag Integrating Bottom-up and Top-down Classification in a Social Tagging System IA Summit 2007 22-26 March, Las Vegas

The Long Tail Our culture and economy is increasingly shifting away from a focus on a relatively small number of "hits" at the head of the demand curve and toward a huge number of niches in the tail
Costs of production fall
Costs of storage and distribution fall
We need better filters and aggregators

The UGC Era
Among adults, 35% of internet users have created content and posted it online
User generated content can be anything produced by the user: text, audio, video, photos, categories or ranks, clips
(PEW, December 2005)

Information Overload
601 exabytes in 2010
70 percent of the world's digital data will be created by individuals
(IDC 2007)
185 exabytes (billion gigabytes) of storage needed last year
12 stacks of books that each reach from the Earth to the Sun
3 million times the information in all the books ever written
more than 2 billion of the most capacious iPods

How can we navigate and find this information?

An Emerging Approach to Distributed Classification
Collaborative tagging systems to organize, browse and share personal collections of resources through the introduction of simple metadata
Folksonomy = user-generated classification, emerging through bottom-up consensus
The basic idea is simply to make people share items annotated with keywords

Del.icio.us Homepage

Collaborative Tagging Examples
An incomplete list of tagging systems
They are web-based collaborative systems for:
building a shared database of items
a flat metadata vocabulary
metadata driven queries
to monitor change in areas of interest
discover emergencies or trends

Have tagging systems solved the issue?

Del.icio.us Homepage

Del.icio.us Tagcloud

Food Tag in Del.icio.us

Down the Long Tail TAG CLOUDS HITS LONG TAIL ?

More Tags for the Same Thing

How many apples? VS VS VS

Folksonomies ’ Properties
Pros
Trade-off between simplicity and precision
Matching users’ real needs and language
They are inclusive (nothing is left out)
Discovery of information and Serendipity
A forced move (the environment makes the difference)
Better than nothing (when traditional classification is not viable)
Cons
Language related issues
User Experience issues

Language Issues
As a result of intrinsic language variability, tagging systems are also implicitly plagued by:
Polysemy (window: the hole or the pane of glass)
Homonymy (apple, jaguar)
Plurals (blog/blogs, folksonomy/folksonomies)
Mistyped tags (folsonomy)
Synonymy (tags, tagging, folksonomy)
Ego-oriented tags (toread, funny, interesting etc..)
Basic level variations (dog/beagle)
These problems can dramatically reduce the effectiveness of the application and the benefits brought on by tagging systems.

User Experience Issues
Low findability quotient and Low scalability
High semantic density (very few well-known topics dominating the scene)
An alphabetical criterion limits the ability to explore the tag cloud
A flat tag cloud cannot visually support semantic relationships
Tag clouds are visual interfaces for information retrieval that provide a global contextual view of tags assigned to resources in the system
Flat tag clouds not sufficient to provide a semantic and multidimensional browsing experience

Navigating Large Domains
Information seekers in large domains of objects express the desire of having to deal with meaningful groupings of related items, in order to quickly understand relationships and decide how to proceed [Marti Hearst 2006].
How to generate and navigate such groups from a flat set of objects is anyway a different matter.
Taxonomies, Clustering and Faceted Classification have been proposed in the past as useful techniques

Our Toolbox!

Taxonomies
Taxonomies = coherent and complete system of meaningful labels which systematically organize a domain
Organically crafted before starting to catalogue trying to guess user needs and content types
Authoritative centralized view
High precision avoiding ambiguity, hierarchical structure to give context
Main drawbacks:
An a priori and monolithic hierarchical organization do not have the ability to match the vocabulary and the varied ways of thinking of different users.
Expensive to build and maintain by professional indexers

Clusters
Clustering = the act of grouping items according to some measure of similarity
It reduces the semantic density and improve the visual consistency of tag clouds
But it generate messy groups , conflate many different dimensions and does not allow refinement and follow-up queries
Users prefer clear hierarchies with categories at uniform levels of granularity over the messy, unpredictable and unlabeled groupings typical of clustering techniques

Facets
Facets = orthogonal descriptors (categories) within a metadata system
Each facet has a name and addresses a different conceptual dimension or feature type relevant to the collection
Each object is classified combining labels from different facets.
Facets can be :
Flat or hierarchical
Assigned single or multiple values
It is hierarchial Facet name 393 resources here

Facets
add structure and context to tags
navigate along several dimensions simultaneously
seamlessly integrate browsing and searching
refine and broaden filtering criteria
Benefits
Hierarchical faceted metadata can be used to
Better support for exploration , discovery and iterative query refinement.
Easier to understand the meaning of tags
Large tag clouds more browsable
Reduction of the mental work (favoring recognition over recall)
Usability studies show how this approach is preferred over single hierarchies and clusters

What do we need next?

What do we need yet?
Middle ground (between the pure democracy of bottom-up tagging and the empirical determinism of top-down controlled vocabularies*)
Metadata ecology : merge and leverage emerging and traditional tools to improve findability
Metadata ecology as a fusion not only a coexistence
*Alex Wright: http://www.agwright.com/ blog / archives /000900.html

FaceTag Contributions
FaceTag tries to limit the impact of polysemy, homonymy and basic level variation introducing a multidimensional and more semantic paradigm
Goals : improving usability, findability, browsability, serendipity and scalability of the system.
FaceTag mixes three contributions to social tagging systems:
Tag hierarchies
Facets of Tags
Tagging and searching mixed

Faceted Analysis

How to choice facets? 2 main roads
Freehand made
Each facet is created at the moment
The subject is freely deconstructed in several aspects
Standard based
Each facet is chosen using the guidelines fixed by Ranganathan or CRG
The subject is deconstructed following a “general scheme”
“ General scheme” works as a prototype of every particular faceted scheme

Facets derived from the CRG general scheme Date Time [Country] Space People Agent Purposes, [Markets] (e.g. Industry, Health ...) Patient -- By-product Deliverables Product [Activities] Operation -- Process Themes Material Language Property -- Part Resource Types (e.g. online report, case study, blog...) Type [Documents, Resources] Thing FACETAG CRG

FaceTag facets date of publication (through a calendar) Date public administration health, education > conferences > www2006 Purposes Weinberger e. Reiss Morville People competitive analysis classification > facets web 2.0 > folksonomies information design > navigation design > breadcrumbs Themes predefined values (select box ISO Standard ISO 639-2) Language white paper case study blog > enterprise web Resource Types SAMPLES FACETAG FACET

The Real Application

FaceTag Home SEARCH + TAG SUGGESTION FACETS + FACETED TAGS RESULT SET

Search Term Selected SEARCH TERM UPDATED TAGS UPDATED RESULT SET

Search Term + Tag Selection FACET TAGS for this FACET FACETED BREADCRUMBS UPDATED RESULT SET

Final Step UPDATED TAGS RESULT SET

Input Form WYSIWYG EDITOR FACETS TITLE and URL HIERARCHICAL TAG SUGGESTION

Preliminary User Research

Preliminary facets were derived from the CRG schema
These facets will be revised through an iterative bottom-up (card sorting) process
The goal: to elicit the best facets from a wide set of IA bookmarks already online
Facets Evaluation

An intuitive, easy to learn and easy to use interface is probably the single most effective way to support and stimulate participation
The new user interface has been designed through documented heuristics and patterns
Verified at each iterative step by small usability tests .
Critical task: the assignment of new bookmarks and the association of tags to relevant facets.
User Interface Evaluation

Conclusions

Folksonomies are dead. Long Life to folksonomies
Low Benefit & Mainstream Ready?
28% of online Americans tag content (PEW December 2006)
Tagging is commoditized, but it has a long way to go
A few ideas with FaceTag
Hierarchies Facets Tag Suggestion Hierarchical Clustering Tagging Decay Advanced Navigation Synonyms Syntax Control User Ratings

Thanks for your time!
www.facetag.org
FaceTag Crew
Emanuele Quintarelli ( [email_address] )
Andrea Resmini (root@resmini.net)
Luca Rosati ( [email_address] )
Luca Mascaro (info@lucamascaro.info)
Diego La Monica (diego.lamonica@gmail.com)
Questions ?

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FaceTag at IASummit 2007

by Emanuele Quintarelli on Mar 26, 2007

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FaceTag at IASummit 2007 — Presentation Transcript