Stimulating High Quality Social Media through Knowledge Barter-Auctioning

Qijin Ji, Haifeng Shen, Yuqing Mao, Yanqin Zhu

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    Incentives play a pivotal role in stimulating user-generated content (UGC), which is critical to the viability and success of today's social computing services. Non-financial social incentives are generally effective in boosting the quantity, but have limited effect on the quality. Conversely, financial incentives generally motivate better quality, but often complicate the efforts to attract quantity. In this paper, we propose knowledge barter-auctioning, a non-financial remunerative mechanism that is particularly effective in stimulating the quality of UGC yet without detriment to its quantity. This mechanism provides an optimal way for the knowledge vendor to choose the best barter partner in order to maximise their expected revenue, which is an extrinsic motivation for the triumph of quality as UGC of higher quality will enable the vendor to attract more bidders and consequently make a higher revenue through the barter auction. We have conducted a series of experiments using a real-world dataset to analyse the ramifications of UGC quality in knowledge bartering processes.

    Original languageEnglish
    Title of host publicationSocialCom '14
    Subtitle of host publicationProceedings of the 2014 International Conference on Social Computing
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Number of pages8
    ISBN (Electronic)9781450328883
    ISBN (Print)9781450328883
    DOIs
    Publication statusPublished - 4 Aug 2014
    EventThe Seventh ASE International Conference on
    Social Computing: SocialCom '14
    - Tsinghua University, Beijing, China
    Duration: 4 Aug 20147 Aug 2014
    Conference number: 7
    https://dl.acm.org/doi/proceedings/10.1145/2639968

    Publication series

    NameACM international conference proceedings series
    PublisherAssociation for Computer Machinery

    Conference

    ConferenceThe Seventh ASE International Conference on
    Social Computing
    CountryChina
    CityBeijing
    Period4/08/147/08/14
    Internet address

    Bibliographical note

    This paper is authored by an employee(s) of the United States Government
    and is in the public domain. Non exclusive copying or redistribution is allowed, provided that the article citation is given and the authors and agency
    are clearly identified as its source

    Keywords

    • Bartering
    • Incentive
    • Optimal auction
    • User-generated content

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