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Evolving Folksonomies Complexity Theory & Folksonomies
Tom ReamyChief Knowledge Architect
KAPS Group
Knowledge Architecture Professional Services
http://www.kapsgroup.com
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Agenda
Introduction– What are Folksonomies?– Advantages and Disadvantages of Folksonomies
Complexity Theory and Folksonomies– Environment, Evolutionary Mechanisms– Intelligent Design: Universe of Discourse
Conclusion– Possible Scenario’s for Evolving Order– Research Directions– Benefits
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KAPS Group
Knowledge Architecture Professional Services (KAPS) Consulting, strategy recommendations Knowledge architecture audits Partners – Convera, Inxight, FAST, and others Taxonomies: Enterprise, Marketing, Insurance, etc.
– Taxonomy customization Intellectual infrastructure for organizations
– Knowledge organization, technology, people and processes– Search, content management, portals, collaboration,
knowledge management, e-learning, etc.
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What are Folksonomies?
Wikipedia: A folksonomy is an Internet-based information retrieval methodology consisting of collaboratively generated, open-ended labels that categorize content such as Web pages, online photographs, and Web links.
A folksonomy is most notably contrasted from a taxonomy – done by users, not professionals,
Example sites – Del.icio.us and Flickr (not really – no feedback)
It is just metadata that users add Key – social mechanism for seeing other tags
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Advantages of Folksonomies
Simple (no complex structure to learn)– No need to learn difficult formal classification system
Lower cost of categorization– Distributes cost of tagging over large population
Open ended – can respond quickly to changes Quality – “compare favorably with professional”? Relevance – SME generated, close to content
– User’s own terms
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Advantages of Folksonomies
Aboutness – qualitative judgments– Reflect user’s perspective
Multiple dimensions – “communities” of like minded taggers Support serendipitous form of browsing Easy to tag any object – photo, document, bookmark Better than no tags at all
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Disadvantages of Folksonomies
They don’t work very well – polysemy, synonyms, etc.– Focus on easy tagging, not finding
Compare favorably with no tags, not controlled vocabularies No structure, no conceptual relationships
– Flats lists do not a onomy make
Jargon – SME’s talking to themselves or each other– Multiple communities – different terms
SME’s are not info professional – different skill Based on popularity only, no quality control
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Disadvantages of Folksonomies
Issues of scale – popular tags already showing 10,000’s of hits Limited applicability – only useful for non-technical or non-
specialist domains Either personal tags (other’s can’t find) or popularity tags – lose
interesting terms (Power law distribution) Errors – misspellings, single words or bad compounds, single use
or idiosyncratic use Wikipedia article – very shallow, “wrong”? – not a taxonomy at all
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Complexity Theory (abridged)History
An interdisciplinary method– Applied to math, model systems, economics, ecology, etc.
Initial Hype Period – 1980’s-1990’s– Chaos theory, Catastrophe theory, AI, etc.
Current – half way between hype and practical– Beware articles that focus on one aspect – self-organizing
Santa Fe Institute, social research, our Keynote The Center for Complex Systems Research
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Complexity Theory (abridged)Examples
Complex Systems (not complicated)– Large number of independent relatively dumb elements
interact according to a small set of rules.– Self-organizing – order emerges– Local rules, local interactions – global order emerges
Definition by Example– Ant Colonies – clear tunnels with no idea of how to clear a
tunnel– Neighborhoods – create a structure with no central planning
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Complexity Theory (abridged)Essential Features
Large numbers of elements Local Interactions Emergence – global from local Feedback Self-organization
– Key idea – often over-hyped
Importance of the environment– Often overlooked
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Complexity Theory and FolksonomiesIntelligent Design – Universe of Discourse Complexity – need right level of structure and disorder No evolution without:
– Initial complex structure– Evolutionary mechanisms – feedback with consequences
Level of structure = value of order that emerges– Color clumps, ants, neighborhood stores
Need to pay attention to initial organization structures– - “taxonomies” and metadata– Communities – users and designers
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Complexity Theory and FolksonomiesDesigning the world Wikipedia – fast cheap encyclopedia
– Not really just mass of workers making local decisions– Role of initial environment and sets of rules – Feedback everywhere - including on structure and rules– Still have designers – administrators, councils of administrators
Editor Team – like Wikipedia– Create the structured environment– Create the rules and feedback system– Tweak the evolution of the system– Analyze data, paths to monitor– Develop initial candidates – interviews, search log analysis,
ethnographic studies
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Complexity Theory and Folksonomies:Two domains – Internet and Internal – Intranet, databases Internet – this is the normal domain for folksonomies
– More content, more users/taggers– Wilder environment– Less specific targets – web sites, topical articles– Large general sites best, not specialty sites
Internal– More initial structure, more similar content– More resources for tagging– More rewards for categorization– Need authority – corporate policy– More precise targets
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Complexity Theory and Folksonomies:Two domains of evolution Structure of the folksonomies
– Bottom up – create clusters – based on co-occuring terms, other, groups of people?
– Social – have people categorize the tags and then have people rank the appropriateness of categories
– One possibility – community based agreement – more people rank a category as good – they become a community
Appropriate tags on documents– Social - Wikipedia style – everyone can tag any document
• Include evolutionary rank for taggers– Everyone can rank the appropriateness of tags– Develop rank of taggers – super-editors, editors, authors
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Complexity Theory and Folksonomies:Evolutionary Mechanisms Feedback with Consequences
– If an ant fails to follow a rule, it dies– Set up minimum number of good category or good tag ranks
by everyone – if below, it dies.– Death of tag/category – deleted or moved to unranked
primordial goo Filter to top – popularity, Tag Clouds – Del.ici.ous
– Very high level – “Blog, photography” Mutation – keywords into other categories, categories into
other categories– Success within a category – popularity, other criteria
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Complexity Theory and Folksonomies Evolutionary Mechanisms Ranking Methods
– Explicit – people rank directly (roles)• Categories, tags, taggers• Good tags, best bets for terms or categories?
– Implicit – software evaluation, reverse relevance Who will rank?
– Interested people, folksonomy advocates– Intranet – rewarded employees– Internet – community sites, aggregators, search engines
What will we call them? – Force of Nature, Deities, Intelligent Designers
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Complexity Theory and Folksonomies Scenario One: Del.icio.us Plus Social tags – only real criteria is popularity – Tag Cloud Evolve quality of tags and emerging structure of tags
– Preferred term = popular (Blog/blogs – Books/book) Add broad general taxonomy of most popular tags
– Tags as natural categories – build up and down Add mechanisms – rank tags, taggers, categories Flickr – facets are natural structure – date, people, events Start – evolve a simple 2 level taxonomy
– People assign tags to a category, build numbers– Evolutionary phase shift – spasm of structure
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Popularity Structure of FolksonomyGood, Bad, and Natural
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Complexity Theory and Folksonomies Scenario Two – Intranet/Content Aggregators
Buy/Build starter taxonomies – more structure than Del.icio.us
Create a team of designers/rules/mechanisms Develop reward structures Feedback – about tags – from employees or customers Feedback about taggers, categories – from central team
with input from selected SME’s. Add evolution to best bets – compete with management
selected
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Complexity Theory and FolksonomiesResearch and Theory
Research Ideas– Uncover the effects of “interwingledness”
• Monitor how people tag (and categorize) – historical patterns
• Who would do this? Institute? Flickr? Other commercial?
• Design new metrics and reports?
– Discover natural category levels• Take terms as candidates for natural level
• Build structure up and down
• Apply communities – different natural levels
• Simplicity – expose taxonomy at natural level - keywords
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Conclusions: Evolutionary Model
Need to design a complex system, not complicated or free form
Different design for four domains: Internet-Internal, Categories-Tags
Advanced feedback is necessary Editor Function is necessary
– Develop infrastructure, analyze feedback, facilitate Order is grown – from a combination of bottom up and
design Management is suggesting rules and testing and gathering
feedback about usefulness, not dictating correct terms
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Complexity Theory and FolksonomiesBenefits
Add the onomy to folk– More structure at low cost
Benefits of research – Investigation itself yields ideas
Internal Domain – supplemented by traditional methods, taxonomies, controlled vocabularies
If it fails, at least could kill the term, foksonomy (It’s metadata)
Questions?
KAPS Group
Knowledge Architecture Professional Services
http://www.kapsgroup.com
