Building Social Trust: A Human-Capital Approach

Huang, Fali

doi:10.1628/093245607783242981

Cited by 22 publications

(18 citation statements)

References 33 publications

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“…As mentioned in [22], trust is a critical factor in the success of SNs adoption. Without trust, members may be reluctant to engage in any form of interaction with peers due to the fears of misjudgment and/or misuse.…”

Section: A Social Trust-aware Recommendation System For Wssmentioning

confidence: 99%

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Towards Improving Recommender System: A Social Trust-Aware Approach

Abderrahim¹,

Benslimane²

2015

IJMECS

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Abstract-Recommender systems have shown great potential to help users find interesting and relevant Web service (WS) from within large registers. However, with the proliferation of WSs, recommendation becomes a very difficult task. Social computing seems offering innovative solutions to overcome those shortcomings. Social computing is at the crossroad of computer sciences and social sciences disciplines by looking into ways of improving application design and development using elements that people encounter daily such as social networks, trust, reputation, and recommendation. In this paper, we propose a social trust-aware system for recommending Web services (WSs) based on social qualities of WSs that they exhibit towards peers at runtime, and trustworthiness of the users who provide feedback on their overall experience using WSs. A set of experiments to assess the fairness and accuracy of the proposed system are reported in the paper, showing promising results and demonstrating that our service recommendation method significantly outperforms conventional similarity-based and trust-based service recommendation methods.

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Section: A Social Trust-aware Recommendation System For Wssmentioning

confidence: 99%

“…Many trust definitions exist depending on the discipline such as sociology [25], psychology [26], economics [22], and computer sciences [27]. In general, trust is a measure of confidence that an entity will behave as expected despite the lack of ability of monitoring this entity [28].…”

Section: Social Trust Networkmentioning

confidence: 99%

Towards Improving Recommender System: A Social Trust-Aware Approach

Abderrahim¹,

Benslimane²

2015

IJMECS

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“…Importantly, positive and negative emotions are the main categories to describe emotions. Trust has been studied in many disciplines including sociology, psychology, economics, and computer science [13,14,15,16]. Each of these disciplines has defined and considered trust in using online social network from different perspectives, but their definitions may not be directly applicable to social networks.…”

Section: Emotion and Trustmentioning

confidence: 99%

“…First, technology acceptance model (TAM) argues that behavioral intention is influenced by psychological status that mainly includes various types of emotion, such as inspired, upset, active, hostile, etc. Second, trust has been studied in many disciplines including sociology, psychology, economics, and computer science [13,14,15,16,22]. And, there are literatures that illustrate the relationship between trust and OSN adoption in SNSs fields [17,18,19,20,21].…”

Section: Introductionmentioning

confidence: 99%

Effects of Emotion and Trust on Online Social Network Adoption toward Individual Benefits: Moderating Impacts of Gender and Involvement

Tsai

Chao

2014

Communications in Computer and Information Science

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Abstract. For the past decade, the advanced development of Online Social Network (OSN) has demonstrated a considerable contribution to the industries and society. The current research proposes and examines the research models that incorporate types of emotion and trust as the antecedents of OSN adoption to describe individual benefits (IB) for positive emotion (PE) and negative emotion (NE) groups. A salient consideration is to examine the moderating effects of gender and involvement on the relationships between independent and dependent variables for both groups. Based on the analysis of 522 valid samples, research results show that (1) for PE group, attentive and active show significant effects on OSN adoption, respectively. (2) for NE group, only ashamed presents a significant influence on OSN adoption. (3) moderators of PE group report that alert, attentive, and active are significant, indicating that female reveals significant effects while male reveals insignificant effects for both alert and attentive, and low involvement reveals significant effects for inspired and active while high involvement reveals significant effects for attentive and active. (4) moderators of NE group report that upset, ashamed, and afraid are significant, indicating that female reveals a significant effect for upset while male reveals a significant effect for ashamed, and high involvement shows significant effects for both ashamed and afraid. Discussion and implications are also addressed.

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“…The concept of trust has been studied in many disciplines including sociology [11], psychology [12], economics [13], and computer science [16]. Each of these disciplines has considered trust from different perspectives.…”

Section: Introductionmentioning

confidence: 99%

STrust: A Trust Model for Social Networks

Nepal

Sherchan

Paris

2011

2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications

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We propose a trust model for social networks with the aim of building trust communities that inspire members to share their experiences, feelings and opinions in an open and honest way without the fear of being judged. The unique feature of our model is that the trust value is derived from the social capital built in the social networks over a period of time. First, we introduce a framework for building trust communities using social trust. We then define an underlying social trust model, called STrust. Finally, we report the current state of the development and the analysis of the proposed trust model.

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Building Social Trust: A Human-Capital Approach

Cited by 22 publications

References 33 publications

Towards Improving Recommender System: A Social Trust-Aware Approach

Towards Improving Recommender System: A Social Trust-Aware Approach

Effects of Emotion and Trust on Online Social Network Adoption toward Individual Benefits: Moderating Impacts of Gender and Involvement

STrust: A Trust Model for Social Networks

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