A Computational Trust Framework for Social Computing (A Position Paper for Panel Discussion on Social Computing Foundations)

Zhan, Justin; Fang, Xing

doi:10.1109/socialcom.2010.44

Cited by 5 publications

(1 citation statement)

References 23 publications

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“…An in depth qualitative analysis of what trust is and what is its role in information science and technology 41 . A computational trust framework for social computing where a trust value can be quantified for a piece of information 42 . Trust in sources which lead to not verifying any news and its relation to the propagation of fake news has also been heavily investigated in a number of studies [43][44][45] .…”

Section: Modelling and Analysing Trust In Fake News Domainmentioning

confidence: 99%

A cognitive behaviour data analysis on the use of social media in global south context focusing on Bangladesh

Samya

Tonmoy

Rabbi

2023

Sci Rep

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This study aimed to investigate the factors that contribute to the propagation of COVID-19 vaccine misinformation on social media in Bangladesh. We attempted to identify the links between the propagation of misinformation and the factors associated with trust in sources based on personal ties among our respondents. In order to find our targeted outcomes, we used a cognitive method in our survey. A total of 202 replies were chosen for analysis, in which respondents were presented with falsified news and asked how they would react to it being shared or posted by someone with whom they have a personal connection. The survey also recorded a variety of other parameters. The Likert Chart Scale was our primary method of data collection, with Yes/No responses serving as a secondary option. The responses were analysed using statistical methods such as Chi-Square Tests, data visualizations and the Ordinal Logistic Regression Model. Our findings have shown that trust in the source can lead to hastily sharing news on social media platforms without proper verification. Other key factors, such as time spent on social media platforms and the type of content shared, also contribute to the propagation of fake news on social media platforms. Such findings may contribute to making Bangladesh more safe and secured in the cyberspace area.

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Section: Modelling and Analysing Trust In Fake News Domainmentioning

confidence: 99%

A cognitive behaviour data analysis on the use of social media in global south context focusing on Bangladesh

Samya

Tonmoy

Rabbi

2023

Sci Rep

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How to Optimize Social Network Influence

Zhan¹

2019

2019 IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)

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A behavior statistic based secure system in social networks

Deng

2012

2012 IEEE International Conference on Computer Science and Automation Engineering

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In order to protect the normal operation of social networks from the influence of malicious communication, we established a system to help evaluate information and users. On one hand, based on behavior recognition technology, the information model uses the specific information's operation data as one of the information's special features to analyze its reliability. On the other hand, to minimize the impacts of some identity's malicious use, we use a two-dimensional algorithm, identifying the users' abnormal behaviors through comparison, as our user model. Our system can effectively reduce malicious communication by identifying malicious information and users in social networks.

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A Computational Trust Framework for Social Computing (A Position Paper for Panel Discussion on Social Computing Foundations)

Cited by 5 publications

References 23 publications

A cognitive behaviour data analysis on the use of social media in global south context focusing on Bangladesh

A cognitive behaviour data analysis on the use of social media in global south context focusing on Bangladesh

How to Optimize Social Network Influence

A behavior statistic based secure system in social networks

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