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A network-centric approach for estimating trust between open source software developers
2019
PLoS ONE
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Second, we infer indirect trust between developers who have not interacted previously by constructing a community-wide developer network and propagating trust in the network. ...
Our two-fold approach, first, computes direct trust between developer pairs who have interacted previously by analyzing their interactions via natural language processing. ...
We compute the aggregate belief (B A D ) and uncertainty (U A D ) from A toward D via one of the following strategies. • The AP-Mean strategy computes aggregate trust as the mean of trust values propagated ...
doi:10.1371/journal.pone.0226281
pmid:31887172
pmcid:PMC6936801
fatcat:sjla5rnlibeg7olsowkperz3da
Trust prediction using positive, implicit, and negative information
2014
Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion
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The proposed method considers positive, implicit, and negative information of all users in a network based on belief propagation to predict trust relationships of a target user. ...
We propose a novel method to predict accurately trust relationships of a target user even if he/she does not have much interaction information. ...
To solve the problem, we propose a novel trust prediction method using belief propagation (BP) [4] . ...
doi:10.1145/2567948.2577288
dblp:conf/www/JangFK14
fatcat:u6vgaldrh5b6zbwtp2vzmzb6tm
SybilFuse: Combining Local Attributes with Global Structure to Perform Robust Sybil Detection
[article]
2018
arXiv
pre-print
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structure via weighted random walk and loopy belief propagation mechanisms. ...
SybilFuse adopts a collective classification approach by first training local classifiers to compute local trust scores for nodes and edges, and then propagating the local scores through the global network ...
Weighted Trust Score Propagation Score propagation is done through either weighted random walk or weighted loopy belief propagation. ...
arXiv:1803.06772v3
fatcat:jqkplctjergybg5g63kjmtzoni
Propagation of trust and distrust
2004
Proceedings of the 13th conference on World Wide Web - WWW '04
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We show that a small number of expressed trusts/distrust per individual allows us to predict reliably trust between any two people in the system with high accuracy: a quadratic increase in actionable information ...
Our work appears to be the first to incorporate distrust in a computational trust propagation setting. ...
From our definition, it is clear that each P (k) captures the propagation of trust or distrust via "paths" of length k. ...
doi:10.1145/988672.988727
dblp:conf/www/GuhaKRT04
fatcat:om3mcm4jjncwpmpyzmbphcieqm
User Trust Inference in Online Social Networks: A Message Passing Perspective
2022
Applied Sciences
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A message passing algorithm, loop belief propagation, is applied to the model inference, which greatly improves the interpretability of the proposed model. ...
Using only explicit yet sparse trust relationships to predict user trust is inefficient in large online social networks. ...
The same above-mentioned trust propagation strategies of direct trust propagation and transposed trust propagation were also leveraged in [28] , which helped the researchers build a better trust prediction ...
doi:10.3390/app12105186
fatcat:z3x255r6snebnprv6kdpxe4b6m
Cognitive Identity Management: Risks, Trust and Decisions using Heterogeneous Sources
2019
2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI)
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Inference engine is a causal network that uses various uncertainty metrics and reasoning mechanisms including Dempster-Shafer and Dezert-Smarandache beliefs. ...
This work advocates for cognitive biometric-enabled systems that integrate identity management, risk assessment and trust assessment. ...
It provides a wide range of tools for risk and trust assessment, as well as prediction via inference on the causal network. ...
doi:10.1109/cogmi48466.2019.00014
dblp:conf/cogmi/YanushkevichHCO19
fatcat:x3dkzauivrdhfakby64sjdfg6i
Mobile social network based trust authentication
2012
2012 The 11th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net)
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For safety, messages are often encrypted and the source is authenticated via PKI, preventing repudiation. ...
In this paper we review the construction of a trust graph in a social network like Facebook. ...
We evaluate the scheme on a large social network and investigate the performance via trust propagation. ...
doi:10.1109/medhocnet.2012.6257109
dblp:conf/medhocnet/LuSWG12
fatcat:2hlc7c3xjnextepw7avmoyhz4y
Evidence-based trust
2010
ACM Transactions on Autonomous and Adaptive Systems
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This paper understands an agent Alice's trust in an agent Bob in terms of Alice's certainty in her belief that Bob is trustworthy. ...
Existing approaches either ignore evidence or only partially address the twin challenges of mapping evidence to trustworthiness and combining trust reports from imperfectly trusted sources. ...
As Section 4.5 shows, Hang et al. find that operators based on our approach yield superior predictions of propagated trust than some conventional approaches. ...
doi:10.1145/1867713.1867715
fatcat:7opgosgi3ffivbwdl3725dyihy
Conceptualizing Distrust Model with Balance Theory and Multi-Faceted Model for Mitigating False Reviews in Location-Based Services (LBS)
2019
Symmetry
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The concept of both trust and distrust are essential criteria of any trust management model to measure the reliability of LBS applications. ...
The results show that distrust is not a negation of trust. ...
Algorithm 3 : 3 Trust Propagation Algorithm Input: Belief Matrix, B Output: Propagated Trust Matrix, P 1. Define the belief matrix, B 2. Case 1: Trust Only 3. Case 2: One-Step Distrust 4. ...
doi:10.3390/sym11091118
fatcat:tgkri6rzcfbo7i6ex7ccurk5na
There Is Hope After All: Quantifying Opinion and Trustworthiness in Neural Networks
2020
Frontiers in Artificial Intelligence
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DeepTrust also provides a projected trust probability of NN's prediction, which is useful when the NN generates an over-confident output under problematic datasets. ...
Also trust probability does not necessarily correlate with accuracy. ...
A subjective trust network represents trust and belief relationships from agents, via other agents or sources to target entities/variables, where each trust and belief relationship is expressed as an opinion ...
doi:10.3389/frai.2020.00054
pmid:33733171
pmcid:PMC7861320
fatcat:lz6ltrffejecjkbdfiypoxspxy
A belief propagation based recommender system for online services
2010
Proceedings of the fourth ACM conference on Recommender systems - RecSys '10
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The belief propagation algorithm relies on a graph-based representation of an appropriately chosen factor graph for the recommender systems. ...
We provide an evaluation of BPRS via computer simulations using the MovieLens dataset. We observed that BPRS iteratively reduces the error in the predicted ratings of the users until it converges. ...
We introduce the "Belief Propagation Based Iterative Recommender System" (BPRS). ...
doi:10.1145/1864708.1864751
dblp:conf/recsys/AydayF10
fatcat:hkgew3litvfvzbednx4ldsifai
Propagating and Debunking Conspiracy Theories on Twitter During the 2015–2016 Zika Virus Outbreak
2018
Cyberpsychology, Behavior, and Social Networking
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Acknowledgments This study was funded by the British Academy/Leverhulme Trust Small Grants Scheme, grant number SG161736. ...
predictions from prior research on conspiracy belief. ...
Surprisingly, and contrary to predictions, propagator tweets also made more explicit references to sources for their claims. ...
doi:10.1089/cyber.2017.0669
pmid:30020821
pmcid:PMC6094351
fatcat:2dbfxh5uajee7a3elsq53q5m5e
When the Bad is Good and the Good is Bad: Understanding Cyber Social Health Through Online Behavioral Change
2021
IEEE Internet Computing
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Propagation of misinformation across different platforms poses challenges to measure trust and capture provenance for information. ...
PROVENANCE Gradually minimizing the spread of incorrect beliefs via introducing corrective information has been found useful. 15 Sources of corrective information are mainstream news media, certain ...
doi:10.1109/mic.2020.3045232
fatcat:wbtqus5blzf3rbh5x75vfeirh4
Assessing Risks of Biases in Cognitive Decision Support Systems
[article]
2020
arXiv
pre-print
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[4] , [19] , as well as trust prediction and belief propagation [20] . ...
The details are highlighted in Section IV via an experiment. Section V concludes the paper.
II. ...
arXiv:2007.14361v1
fatcat:g36n75gr7jbplkrpzmnshug2h4
A Classification of Trust Computation Models for Service-Oriented Internet of Things Systems
2015
2015 IEEE International Conference on Services Computing
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Our approach is to classify existing trust computation models based on five design dimensions: trust composition, trust propagation, trust aggregation, trust update, and trust formation. ...
Future Internet of Things (IoT) systems will connect the physical world into cyberspace everywhere and everything via billions of smart objects and are expected to have a high economic impact. ...
Trust Propagation Trust propagation refers to how to propagate trust evidence to peers. In general, there are two trust propagation schemes -that is, distributed and centralized. ...
doi:10.1109/scc.2015.52
dblp:conf/IEEEscc/GuoC15
fatcat:praozypswvdxhokuhgiar2uexi
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