Dynamics of online peer production and collaborative sensemaking
This event took place on Tuesday 02 November 2010 at 12:00
Dario Taraborelli Centre for Research in Social Simulation at the University of Surrey
This talk consists of two parts: the first part focusses on a study of the dynamics of online peer production systems; the second discusses crowdsourcing strategies to semantically structure a large body of knowledge.
Despite a large interest in the research community for online peer production, little has been done to study the dynamics of online communities that form part of larger ecosystems, and in particular what determines the performance and ultimately the survival of individual collaborative communities within such an ecosystem. This is partly due to the lack of large-scale data on the temporal evolution of collaborative ecosystems, partly to a poor understanding of what it means for communities that form these ecosystems to be "viable". Studying how these communities evolve over time can help us understand the determinants of their growth and assess their viability as a function of their social structure, internal functioning and relationship with competing communities. In this talk I present two case studies looking at community dynamics in the context of the wiki and social media ecosystem. I also present a tool called WikiTracer whose goal is to help us collect in a standardised way detailed data on wiki-based communities from a variety of heterogeneous platforms.
The second part of this presentation describes the CrowdLinks project, a proposed framework to allow large populations of users to semantically annotate the relationship between scholarly articles. Online reference management services offer a unique opportunity to add a collaborative semantic layer on top of a citation network. In this talk I present the rationale, design and expected outcome of this framework and discuss how collaborative citation typing can help us better understand the structure and progress of scientific research.
This event took place on Tuesday 02 November 2010 at 12:00
This talk consists of two parts: the first part focusses on a study of the dynamics of online peer production systems; the second discusses crowdsourcing strategies to semantically structure a large body of knowledge.
Despite a large interest in the research community for online peer production, little has been done to study the dynamics of online communities that form part of larger ecosystems, and in particular what determines the performance and ultimately the survival of individual collaborative communities within such an ecosystem. This is partly due to the lack of large-scale data on the temporal evolution of collaborative ecosystems, partly to a poor understanding of what it means for communities that form these ecosystems to be "viable". Studying how these communities evolve over time can help us understand the determinants of their growth and assess their viability as a function of their social structure, internal functioning and relationship with competing communities. In this talk I present two case studies looking at community dynamics in the context of the wiki and social media ecosystem. I also present a tool called WikiTracer whose goal is to help us collect in a standardised way detailed data on wiki-based communities from a variety of heterogeneous platforms.
The second part of this presentation describes the CrowdLinks project, a proposed framework to allow large populations of users to semantically annotate the relationship between scholarly articles. Online reference management services offer a unique opportunity to add a collaborative semantic layer on top of a citation network. In this talk I present the rationale, design and expected outcome of this framework and discuss how collaborative citation typing can help us better understand the structure and progress of scientific research.
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We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.
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