research-article

Trust Networks: Topology, Dynamics, and Measurements

Authors:

Alessandro ProvettiAuthors Info & Claims

IEEE Internet Computing, Volume 19, Issue 6

Pages 26 - 35

https://doi.org/10.1109/MIC.2015.93

Published: 01 November 2015 Publication History

Abstract

Thanks to the availability of user profiles and records of activity, online social network analysis can discover complex individual and social behavior patterns. The emergence of trust between users of online services is one of the most important phenomena, but it's also hard to detect in records of users' interactions, and even harder to replicate by abstract, generative models. Here, the authors investigate the emergence of "trusted" users (over time) by studying the evolution of topological and centrality measures of the network of trust within the overall social network. To do so, large datasets of user activity are studied from Ciao and Epinions (two online platforms with an explicit notion of trust controlled by users), and Prosper (a micro-lending site where trust remains implicit). The implications of such findings are discussed, particularly regarding how to enable trust in online platforms and interaction, with implications for trust-based activities.

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Gutierrez CWhittaker APatenio KGehman JLefsrud LBarbosa DStroulia EOnuţ IZulkernine F(2021)Analyzing and visualizing Twitter conversationsProceedings of the 31st Annual International Conference on Computer Science and Software Engineering10.5555/3507788.3507791(4-13)Online publication date: 22-Nov-2021
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Abbaspour Orangi MHashemi Golpayegani A(2021)Finding effective nodes to maximize the trusting behavior propagation in social networksComputing10.1007/s00607-021-00949-3103:12(2995-3016)Online publication date: 1-Dec-2021
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Costantini SDe Meo PGiorgianni AMigliorato VProvetti ASalvia F(2020)Exploring Low-degree nodes first accelerates Network ExplorationProceedings of the 12th ACM Conference on Web Science10.1145/3394231.3397914(241-249)Online publication date: 6-Jul-2020
https://dl.acm.org/doi/10.1145/3394231.3397914
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Trust Networks: Topology, Dynamics, and Measurements

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Published In

IEEE Internet Computing Volume 19, Issue 6

Nov.-Dec. 2015

71 pages

ISSN:1089-7801

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IEEE Educational Activities Department

United States

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Published: 01 November 2015

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Gutierrez CWhittaker APatenio KGehman JLefsrud LBarbosa DStroulia EOnuţ IZulkernine F(2021)Analyzing and visualizing Twitter conversationsProceedings of the 31st Annual International Conference on Computer Science and Software Engineering10.5555/3507788.3507791(4-13)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.5555/3507788.3507791
Abbaspour Orangi MHashemi Golpayegani A(2021)Finding effective nodes to maximize the trusting behavior propagation in social networksComputing10.1007/s00607-021-00949-3103:12(2995-3016)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s00607-021-00949-3
Costantini SDe Meo PGiorgianni AMigliorato VProvetti ASalvia F(2020)Exploring Low-degree nodes first accelerates Network ExplorationProceedings of the 12th ACM Conference on Web Science10.1145/3394231.3397914(241-249)Online publication date: 6-Jul-2020
https://dl.acm.org/doi/10.1145/3394231.3397914
De Meo PLevene MProvetti A(2019)Potential gain as a centrality measureIEEE/WIC/ACM International Conference on Web Intelligence10.1145/3350546.3352559(418-422)Online publication date: 14-Oct-2019
https://dl.acm.org/doi/10.1145/3350546.3352559
Zhan JJiang YMa WLuo XLiu W(2019)A Trust Network Model Based on Hesitant Fuzzy Linguistic Term SetsKnowledge Science, Engineering and Management10.1007/978-3-030-29563-9_26(284-297)Online publication date: 28-Aug-2019
https://dl.acm.org/doi/10.1007/978-3-030-29563-9_26

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Benevolence trust: a key determinant of user continuance use of online social networks

Dynamics of Trust Revision: Using Health Infomediaries

User Trust Dynamics: An Investigation Driven by Differences in System Performance

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