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Propagation Models for Trust and Distrust in Social Networks

Author

Listed:
  • Cai-Nicolas Ziegler

    (Universität Freiburg, Georges-Köhler-Allee)

  • Georg Lausen

    (Universität Freiburg, Georges-Köhler-Allee)

Abstract

Semantic Web endeavors have mainly focused on issues pertaining to knowledge representation and ontology design. However, besides understanding information metadata stated by subjects, knowing about their credibility becomes equally crucial. Hence, trust and trust metrics, conceived as computational means to evaluate trust relationships between individuals, come into play. Our major contribution to Semantic Web trust management through this work is twofold. First, we introduce a classification scheme for trust metrics along various axes and discuss advantages and drawbacks of existing approaches for Semantic Web scenarios. Hereby, we devise an advocacy for local group trust metrics, guiding us to the second part which presents Appleseed, our novel proposal for local group trust computation. Compelling in its simplicity, Appleseed borrows many ideas from spreading activation models in psychology and relates their concepts to trust evaluation in an intuitive fashion. Moreover, we provide extensions for the Appleseed nucleus that make our trust metric handle distrust statements.

Suggested Citation

  • Cai-Nicolas Ziegler & Georg Lausen, 2005. "Propagation Models for Trust and Distrust in Social Networks," Information Systems Frontiers, Springer, vol. 7(4), pages 337-358, December.
    • Handle: RePEc:spr:infosf:v:7:y:2005:i:4:d:10.1007_s10796-005-4807-3
    DOI: 10.1007/s10796-005-4807-3
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    Citations

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    Cited by:

    1. Daniel S. Soper & Haluk Demirkan & Michael Goul, 2007. "An interorganizational knowledge-sharing security model with breach propagation detection," Information Systems Frontiers, Springer, vol. 9(5), pages 469-479, November.
    2. Raed S. Algharabat & Nripendra P. Rana, 2021. "Social Commerce in Emerging Markets and its Impact on Online Community Engagement," Information Systems Frontiers, Springer, vol. 23(6), pages 1499-1520, December.
    3. Reema Aswani & Arpan Kumar Kar & P. Vigneswara Ilavarasan, 2018. "Detection of Spammers in Twitter marketing: A Hybrid Approach Using Social Media Analytics and Bio Inspired Computing," Information Systems Frontiers, Springer, vol. 20(3), pages 515-530, June.
    4. Jennifer Golbeck & Jeff Gerhard & Farrah O’Colman & Ryan O’Colman, 2018. "Scaling Up Integrated Structural and Content-Based Network Analysis," Information Systems Frontiers, Springer, vol. 20(6), pages 1191-1202, December.
    5. Yogesh K. Dwivedi & Banita Lal & Navonil Mustafee & Michael D. Williams, 2009. "Profiling a decade of Information Systems Frontiers’ research," Information Systems Frontiers, Springer, vol. 11(1), pages 87-102, March.
    6. Ghassan Beydoun & Babak Abedin & José M. Merigó & Melanie Vera, 2019. "Twenty Years of Information Systems Frontiers," Information Systems Frontiers, Springer, vol. 21(2), pages 485-494, April.
    7. Raed S. Algharabat & Nripendra P. Rana, 0. "Social Commerce in Emerging Markets and its Impact on Online Community Engagement," Information Systems Frontiers, Springer, vol. 0, pages 1-22.
    8. Stephen X. Zhang & Javier Cueto, 2017. "The Study of Bias in Entrepreneurship," Entrepreneurship Theory and Practice, , vol. 41(3), pages 419-454, May.
    9. Xiaolong Zheng & Daniel Zeng & Fei-Yue Wang, 2015. "Social balance in signed networks," Information Systems Frontiers, Springer, vol. 17(5), pages 1077-1095, October.
    10. Rodolfo Baggio, 2011. "The Mechanism for Spreading Online Reputation," Academica Turistica - Tourism and Innovation Journal, University of Primorska Press, vol. 4(2), pages 5-13.
    11. Wei-Lun Chang & Arleen N. Diaz & Patrick C. K. Hung, 2015. "Estimating trust value: A social network perspective," Information Systems Frontiers, Springer, vol. 17(6), pages 1381-1400, December.
    12. Gelan Yang & Qin Yang & Huixia Jin, 2021. "A novel trust recommendation model for mobile social network based on user motivation," Electronic Commerce Research, Springer, vol. 21(3), pages 809-830, September.

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