Participatory Models in Networks, Crowds and Communities
Monday 12th December at 15:30, ICOSS Conference Room (see map).
Seminar from 15:30 until 16:30 with refreshments afterwards. No need to book.
Professor Caroline Haythornthwaite
University of British Columbia
Canada
Bio:
Professor Haythornthwaite is Director, School of Library, Archival and Information Studies, University of British Columbia. She joined UBC in 2010 after 14 years at the University of Illinois at Urbana-Champaign, where she was Professor in the Graduate School of Library and Information Science. In 2009-10, she was Leverhulme Trust Visiting Professor at the Institute of Education, University of Londonpresenting and writing on learning networks; and in summer 2009 she was a visiting researcher lecturing on distributed knowledge, social networks, and e-learning at the Brazilian Institute for Information in Science and Technology (IBICT), Rio de Janeiro, Brazil. She has an international reputation in research on information and knowledge sharing through social networks, and the impact of computer media and the Internet on work, learning and social interaction.
Talk:
This research presents a Social Network perspective on online peer production, identifying "crowds" and "communities" as two ends of acontinuum of contributory behaviour. Peer production, it is argued,seems to operate on two distinct models – a crowdsourcing modelbased on micro-participation from many, unconnected individuals, and a virtual community model, based on strong connections among a set ofstrongly committed members. At one end of the scale, `lightweight´ collaboration is characterized by low interpersonal commitment, yetstrong investment in a common interest or purpose. At the `heavyweight´ end of the scale, strong interpersonal connectionsoperate with strong-ties with other community members and community purpose. Building on the literature and cases of crowds and virtualcommunities, the presentation defines a set of dimensions that distinguish these two forms of organizing, based on such factors ascontribution type and group size, power structures, and recognition/reward systems.
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