Rational Trust Modeling

2018 ◽  
pp. 418-431 ◽  
Author(s):  
Mehrdad Nojoumian
Keyword(s):  
Trust Modeling

A Semantic Trust Modeling Method for Service Composition

2008 ◽  
Author(s):  
Xiaoqin Xie ◽  
Bailing Du ◽  
Miao Hu ◽  
Zhiqiang Zhang
Keyword(s):  
Service Composition ◽  
Modeling Method ◽  
Trust Modeling

Trust Modeling in Cloud

2020 ◽  
pp. 77-93
Author(s):  
Punit Gupta ◽  
Pradeep Kumar Gupta
Keyword(s):  
Trust Modeling

Interpersonal and political trust: modeling levels of citizens' trust

2010 ◽  
Vol 44 (3/4) ◽  
pp. 369-381 ◽  
Author(s):  
Leon Schiffman ◽  
Shawn T. Thelen ◽  
Elaine Sherman
Keyword(s):  
Political Trust ◽  
Trust Modeling

scholarly journals Addressing Misinformation in Online Social Networks: Diverse Platforms and the Potential of Multiagent Trust Modeling

Information ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 539
Author(s):  
Robin Cohen ◽  
Karyn Moffatt ◽  
Amira Ghenai ◽  
Andy Yang ◽  
Margaret Corwin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Social Networks ◽  
Social Networking ◽  
Older Adult ◽  
Online Social Networks ◽  
Social Behaviour ◽  
Data Science ◽  
Science Studies ◽  
Trust Modeling ◽  
The Future

In this paper, we explore how various social networking platforms currently support the spread of misinformation. We then examine the potential of a few specific multiagent trust modeling algorithms from artificial intelligence, towards detecting that misinformation. Our investigation reveals that specific requirements of each environment may require distinct solutions for the processing. This then leads to a higher-level proposal for the actions to be taken in order to judge trustworthiness. Our final reflection concerns what information should be provided to users, once there are suspected misleading posts. Our aim is to enlighten both the organizations that host social networking and the users of those platforms, and to promote steps forward for more pro-social behaviour in these environments. As a look to the future and the growing need to address this vital topic, we reflect as well on two related topics of possible interest: the case of older adult users and the potential to track misinformation through dedicated data science studies, of particular use for healthcare.

Improving Anomaly Detection Error Rate by Collective Trust Modeling

2008 ◽  
pp. 398-399 ◽  
Author(s):  
Martin Rehák ◽  
Michal Pěchouček ◽  
Karel Bartoš ◽  
Martin Grill ◽  
Pavel Čeleda ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Error Rate ◽  
Detection Error ◽  
Trust Modeling ◽  
Collective Trust

Improving trust modeling through the limit of advisor network size and use of referrals

2013 ◽  
Vol 12 (2) ◽  
pp. 112-123 ◽  
Author(s):  
Joshua Gorner ◽  
Jie Zhang ◽  
Robin Cohen
Keyword(s):  
Network Size ◽  
Trust Modeling
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