Curating Collaborative Content Axel Bruns [email_address] KCB202

Why Do You Need to Know This? Career opportunities: opportunities to work in and develop content curation communities growing need for people skilled in managing knowledge and metadata great interest in people able to utilise “coolfinding” communities for viral marketing using user-generated knowledge spaces to keep up with cutting-edge information is a major career skill Major challenges: fast-changing knowledge environments with multiple points of entry many employers not even aware of the need to address these issues some metadata tracking and mining approaches require advanced IT and maths skills

Career opportunities:

opportunities to work in and develop content curation communities

growing need for people skilled in managing knowledge and metadata

great interest in people able to utilise “coolfinding” communities for viral marketing

using user-generated knowledge spaces to keep up with cutting-edge information is a major career skill

Major challenges:

fast-changing knowledge environments with multiple points of entry

many employers not even aware of the need to address these issues

some metadata tracking and mining approaches require advanced IT and maths skills

New Knowledge Structures Produsage creates new forms of content: decentralised, contradictory, diverse – and in large volumes requires new ways of storing, managing, curating this content curation itself organised through produsage: relying on widespread user participation e.g. del.icio.us , Digg , Reddit ; blogs, wikis; Google PageRank … and new forms of metadata: mining of user-generated (prodused) metadata key practices: tagging, linking, browsing (“coolfinding”) – all leave metadata traces plus special interest practices (e.g. Last.fm , iLike for music) development of an all-encompassing “cosmopedia”, curated by all of us (Pierre L é vy ) Curation can rely on combination of deliberate and accidental metadata (Bruns, 171-181)

Produsage creates new forms of content:

decentralised, contradictory, diverse – and in large volumes

requires new ways of storing, managing, curating this content

curation itself organised through produsage: relying on widespread user participation

e.g. del.icio.us , Digg , Reddit ; blogs, wikis; Google PageRank

… and new forms of metadata:

mining of user-generated (prodused) metadata

key practices: tagging, linking, browsing (“coolfinding”) – all leave metadata traces

plus special interest practices (e.g. Last.fm , iLike for music)

development of an all-encompassing “cosmopedia”, curated by all of us (Pierre L é vy )

Curation can rely on combination of deliberate and accidental metadata

(Bruns, 171-181)

Examples Visualising collaborative content curation: social networks on Twitter: used for community support, instant coolfinding e.g. visualisation by Akshay Java identifies lead users in specific fields US political blogger networks: used for political commentary and debate e.g. visualisation by Jodi Dean et al . identifies opinion leaders on specific topics Web rankings: used for finding relevant information through search engines e.g. Google PageRank, del.icio.us , etc. identifies most important content for specific queries

Visualising collaborative content curation:

social networks on Twitter:

used for community support, instant coolfinding

e.g. visualisation by Akshay Java

identifies lead users in specific fields

US political blogger networks:

used for political commentary and debate

e.g. visualisation by Jodi Dean et al .

identifies opinion leaders on specific topics

Web rankings:

used for finding relevant information through search engines

e.g. Google PageRank, del.icio.us , etc.

identifies most important content for specific queries

Folksonomies User-generated ways of categorising content: fluid and changeable rather than predetermined and fixed responsive to participants’ changing views flat (or heterarchical) rather than hierarchical structure not requiring all participants to work together or agree on one shared view but not chaotic: common patterns usually emerge very quickly indicating commonly held views among many users folksonomy: “folk-driven taxonomy” similar to well-worn, “user-generated” paths in a park contrasted with predetermined, paved pathways image by Fort Photo (Bruns, 181-187)

User-generated ways of categorising content:

fluid and changeable rather than predetermined and fixed

responsive to participants’ changing views

flat (or heterarchical) rather than hierarchical structure

not requiring all participants to work together or agree on one shared view

but not chaotic: common patterns usually emerge very quickly

indicating commonly held views among many users

folksonomy: “folk-driven taxonomy”

similar to well-worn, “user-generated” paths in a park

contrasted with predetermined, paved pathways

Folksonomy Effects Folksonomies affect existing knowledge structures: “ By tweaking some of the underlying assumptions behind today's Web, you could design an alternative version that could potentially mimic the self-organising neighborhoods of cities or the differentiated lobes of the human brain – and could definitely reproduce the simpler collective problem-solving of ant colonies. The Web's not inherently disorganized, it's just built that way.” (Stephen Johnson) folksonomic systems make such tweaks and curate Web content, but do not simply replace one classification system with another multiple alternative knowledge structures are now available to Web users e.g. Google , del.icio.us , Wikipedia , specialist portals, etc. and more alternatives can be created by interested produser communities they will be successful if a critical mass of users sees them as worthwhile

Folksonomies affect existing knowledge structures:

“ By tweaking some of the underlying assumptions behind today's Web, you could design an alternative version that could potentially mimic the self-organising neighborhoods of cities or the differentiated lobes of the human brain – and could definitely reproduce the simpler collective problem-solving of ant colonies. The Web's not inherently disorganized, it's just built that way.” (Stephen Johnson)

folksonomic systems make such tweaks and curate Web content,

but do not simply replace one classification system with another

multiple alternative knowledge structures are now available to Web users

e.g. Google , del.icio.us , Wikipedia , specialist portals, etc.

and more alternatives can be created by interested produser communities

they will be successful if a critical mass of users sees them as worthwhile

Future Challenges For users: staying in touch with developments in order to keep up with most useful knowledge sources understanding how to use folksonomic systems to find the best information maintaining awareness of the shortcomings of folksonomic categorisation For industry: managing own status and standing in folksonomic classification systems using folksonomies for viral marketing and information dissemination addressing negative perceptions spreading through these knowledge systems developing effective tools for tracking and mining metadata in folksonomies For society: combining folksonomic and taxonomic systems harnessing information and fighting misinformation in these knowledge systems

For users:

staying in touch with developments in order to keep up with most useful knowledge sources

understanding how to use folksonomic systems to find the best information

maintaining awareness of the shortcomings of folksonomic categorisation

For industry:

managing own status and standing in folksonomic classification systems

using folksonomies for viral marketing and information dissemination

addressing negative perceptions spreading through these knowledge systems

developing effective tools for tracking and mining metadata in folksonomies

For society:

combining folksonomic and taxonomic systems

harnessing information and fighting misinformation in these knowledge systems