The mechanism of trust and distrust formation and their relational outcomes

Cho, Jinsook

doi:10.1016/j.jretai.2005.11.002

Cited by 344 publications

(361 citation statements)

References 25 publications

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“…• Social scientists understand distrust from the perspectives of formation mechanisms and constructs [40,12]. One understanding is that distrust is the negation of trust while an alternative understanding is that distrust has added value over trust.…”

Section: Research Challengesmentioning

confidence: 99%

“…For example, [68,12] claim that trust and distrust help a decision maker reduce uncertainty and vulnerability (i.e., risk) associated with decision consequences; and [13] indicates that only distrust can irrevocably exclude services from being selected at all. There is an enduring problem about distrust -what is the relation between trust and distrust.…”

Section: Distrust In Social Sciencesmentioning

confidence: 99%

“…Social scientists understand distrust from the perspectives of formation mechanisms and constructs [40,12] and have recognized that distrust helps a decision maker reduce the uncertainty and vulnerability (i.e., risk) associated with decision consequences [12], and in some cases, plays a more critical role than trust [68,54].…”

Section: Chapter 3 Understanding Distrust In Social Mediamentioning

confidence: 99%

“…Many recommender systems are proposed to incorporate ones' trust networks for recommendation and gain performance improvement [52,46,27,47,28,82,91]. Scholars have noted that distrust information may be more noticeable and credible than trust information with a similar magnitude [12]. In this section, we investigate how to exploit trust/distrust networks for recommendation [72].…”

Section: Recommendationmentioning

confidence: 99%

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Computing Distrust in Social Media

Tang¹

2015

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A myriad of social media services are emerging in recent years that allow people to communicate and express themselves conveniently and easily. The pervasive use of social media generates massive data at an unprecedented rate. It becomes increasingly difficult for online users to find relevant information or, in other words, exacerbates the information overload problem. Meanwhile, users in social media can be both passive content consumers and active content producers, causing the quality of user-generated content can vary dramatically from excellence to abuse or spam, which results in a problem of information credibility. Trust, providing evidence about with whom users can trust to share information and from whom users can accept information without additional verification, plays a crucial role in helping online users collect relevant and reliable information. It has been proven to be an effective way to mitigate information overload and credibility problems and has attracted increasing attention.As the conceptual counterpart of trust, distrust could be as important as trust and its value has been widely recognized by social sciences in the physical world. However, little attention is paid on distrust in social media. Social media differs from the physical world -(1) its data is passively observed, large-scale, incomplete, noisy and embedded with rich heterogeneous sources; and (2) distrust is generally unavailable in social media. These unique properties of social media present novel challenges for computing distrust in social media: (1) passively observed social media data does not provide necessary information social scientists use to understand distrust, how can I understand distrust in social media? (2) distrust is usually invisible in social media, how can I make invisible distrust visible by leveraging unique properties of social media data? and (3) little is known about distrust and its role in social media applications, how can distrust help make difference in social media applications?The chief objective of this dissertation is to figure out solutions to these challenges i via innovative research and novel methods. In particular, computational tasks are designed to understand distrust, a innovative task, i.e., predicting distrust is proposed with novel frameworks to make invisible distrust visible, and principled approaches are develop to apply distrust in social media applications. Since distrust is a special type of negative links, I demonstrate the generalization of properties and algorithms of distrust to negative links, i.e., generalizing findings of distrust, which greatly expands the boundaries of research of distrust and largely broadens its applications in social media. He is the mentor because I always seek his suggestions and help for many aspects in my life; and he is also my friend because I feel free to share my personal happiness and sadness with him. Dr.Liu, I cannot thank you enough.

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Section: Research Challengesmentioning

confidence: 99%

Section: Distrust In Social Sciencesmentioning

confidence: 99%

Section: Chapter 3 Understanding Distrust In Social Mediamentioning

confidence: 99%

Section: Recommendationmentioning

confidence: 99%

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Computing Distrust in Social Media

Tang¹

2015

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“…Cho (2006) ainda cita que, na área de Administração, de uma forma ampla, a confiança tem sido concebida como a expectativa positiva sobre o comportamento do parceiro de relação. Desta forma, a confiança do cliente, nesta tese, será tratada como um construto que envolve a expectativa positiva sobre o cumprimento de promessas feitas pelo provedor de serviço (LEWICKI et al, 1998;SIRDESHMUKH et al, 2002;CHO, 2006). Considerando a importância da confiança para a qualidade de uma relação, Wang e Huff (2007) citam que a incerteza e a vulnerabilidade são conceitos importantes no surgimento e sustentação da confiança.…”

Section: Confiançaunclassified

Violação E Recuperação Da Confiança Do Cliente Após O Duplo Desvio

Basso

Santos

2014

REGE

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Perceived trustworthiness of online shops

Büttner¹,

Göritz²

2008

J of Consumer Behaviour

171

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Trust has been found to be crucial for consumer behaviour towards online shops. However, existing studies on the role of trust in electronic commerce are mainly based on ad hoc scales to measure trustworthiness, merely rely on self-reported consequences of trust such as intention to buy, and focus on low-risk products. In a web-based study, 634 participants interacted with a provider of medical goods, that is a simulated online pharmacy. The study develops and employs a psychometrically sound scale for assessing perceived trustworthiness of online shops. Moreover, it examines the impact of trustworthiness on both consumers' intended and actual behaviour towards online shops. Results show that trustworthiness promotes both intention to buy and actual financial risk taking. Perceived risk was not found to moderate the relationship between trustworthiness and intention to buy. Instead, trustworthiness partially mediated the influence of perceived risk on intention to buy. The results from the scale development challenge multidimensional conceptualizations of trust; comparing this finding with other studies suggests that the duration of the relationship might moderate the dimensionality of trust.

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The mechanism of trust and distrust formation and their relational outcomes

Cited by 344 publications

References 25 publications

Computing Distrust in Social Media

Computing Distrust in Social Media

Violação E Recuperação Da Confiança Do Cliente Após O Duplo Desvio

Perceived trustworthiness of online shops

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