A Unified Measurement Solution of Software Trustworthiness Based on Social-to-Software Framework

As trust becomes increasingly important in software domain, software trustworthiness — as a complex high-composite concept, has developed into a big challenge people have to face, especially in the current open, dynamic and ever-changing Internet environment. Furthermore, how to recognize and define trust problem from its nature and how to measure software trustworthiness correctly and effectively play a key role in improving users’ trust in choosing software. Based on trust theory in the field of humanities and sociology, this paper proposes a measurable S2S (Social-to-Software) software trustworthiness framework, introduces a generalized indicator loss to unify three parts of trustworthiness result, and presents a whole metric solution for software trustworthiness, including the advanced J-M model based on power function and time-loss rate for ability trustworthiness measurement, the fuzzy comprehensive evaluation advanced-model considering effect of multiple short boards for basic standard trustworthiness, and the identity trustworthiness measurement method based on the code homology detecting tools. Finally, it provides a case study to verify that the solution is applicable and effective.     

The influence of disposition and social ties on trust in new virtual teammates

With the increased presence of social media tools such as LinkedIn and Facebook, social network information is now commonplace. Social media websites prominently display the social distance or so-called “degrees of separation” among users, effectively allowing people to view their shared social ties with others, including prospective teammates they have not met. Through the presentation and manipulation of social network information, this longitudinal experiment investigated whether dispositional and relational variables contribute to “swift trust” among new virtual teammates. Data from 74 participants were collected to test a path analytic model predicting that social ties and propensity to trust influence perceptions of a new teammate’s trustworthiness (ability, benevolence, and integrity) as well as the willingness to trust that new teammate when given the opportunity to do so. Path analysis indicated good model fit, but showed no significant evidence that social ties or propensity to trust affect perceived trustworthiness at the initial point of team engagement. Additionally, only one component of perceived trustworthiness (perceived ability) and propensity to trust were found to predict trusting behavior towards a new, unknown, teammate.     

Trust perceptions of online travel information by different content creators: Some social and legal implications

Consumers are increasingly turning to the online environment to provide information to assist them in making purchase decisions related to travel products. They often rely on travel recommendations from different sources, such as sellers, independent experts and, increasingly, other consumers. A new type of online content, user-generated content (UGC), provides a number of legal and social challenges to providers and users of that content, especially in relation to areas such as defamation, misrepresentation and social embarrassment. This paper reports research that examined the level of trustworthiness of online travel information from these different sources. The study used a survey of Australian travel consumers (n = 12,000) and results support the notion that there are differences in the level of trust for online travel information from different sources. Respondents ‘tended to agree’ that they trusted information provided by travel agents, information from commercial operators and comments made by travellers on third party websites. However, the highest level of trust was afforded to information provided on State government tourism websites. These results suggest that greater trust is placed in online travel comments when they are on a specific travel website than when they are on a more generic social networking website. However, respondents were ‘not sure’ that they trusted comments made by travellers on weblogs and on social networking sites. Some 88% of respondents that had not visited UGC websites (or were unsure if they had) indicated that they thought that UGC would be useful in the future – suggesting that they feel that any concerns they may have in relation to legal and social problems resulting from its use will be resolved.     

The Mind’s Eye on Personal Profiles: A Cognitive Perspective on Profile Elements that Inform Initial Trustworthiness Assessments and Social Awareness in Virtual Project Teams

Collaboration in virtual project teams heavily relies on interpersonal trust, for which perceived professional trustworthiness is an important determinant. In face to face teams colleagues form a first impression of each others trustworthiness based on signs and signals that are ‘naturally’ available. However, virtual project team members do not have the same opportunities to assess trustworthiness. This study provides insight in the information elements that virtual project team members value to assess professional trustworthiness in the initial phase of collaboration. The trustworthiness formed initially is highly influential on interpersonal trust formed during latter collaboration. We expect trustors in virtual teams to especially value information elements (= small containers for personal data stimulating the availability of specific information) that provide them with relevant cues of trust warranting properties of a trustee. We identified a list with fifteen information elements that were highly valued across trustors (n?=?226) to inform their trustworthiness assessments. We then analyzed explanations for preferences with the help of a theory-grounded coding scheme for perceived trustworthiness. Results show that respondents value those particular information elements that provide them with multiple cues (signaling multiple trust warranting properties) to assess the trustworthiness of a trustee. Information elements that provide unique cues (signaling for a specific trust warranting property) could not be identified. Insight in these information preferences can inform the design of artefacts, such as personal profile templates, to support acquaintanceships and social awareness especially in the initial phase of a virtual project team.     

Association of users with software agents in e-commerce

This paper aims at answering three questions related to the association of users with software agents. This association applies to the e-commerce field in which users have online access to several products and services. Such users could delegate their routine and tedious transactions to agents that will be acting on their behalf. Why, how, and when this delegation occurs is discussed in this paper. Agents are considered in e-commerce due to the features that embody them, such as autonomy and mobility.     

Trust and e-commerce: a study of consumer perceptions

Increasing use of the World Wide Web as a B2C commercial tool raises interest in understanding the key issues in building relationships with customers on the Internet. Trust is believed to be the key to these relationships. Given the differences between a virtual and a conventional marketplace, antecedents and consequences of trust merit re-examination. This research identifies a number of key factors related to trust in the B2C context and proposes a framework based on a series of underpinning relationships among these factors. The findings in this research suggest that people are more likely to purchase from the web if they perceive a higher degree of trust in e-commerce and have more experience in using the web. Customer’s trust levels are likely to be influenced by the level of perceived market orientation, site quality, technical trustworthiness, and user’s web experience. People with a higher level of perceived site quality seem to have a higher level of perceived market orientation and trustworthiness towards e-commerce. Furthermore, people with a higher level of trust in e-commerce are more likely to participate in e-commerce. Positive ‘word of mouth’, money back warranty and partnerships with well-known business partners, rank as the top three effective risk reduction tactics. These findings complement the previous findings on e-commerce and shed light on how to establish a trust relationship on the World Wide Web.     

Determining trust in media-rich websites using semantic similarity

Significant growth of multimedia content on the World Wide Web (or simply ??Web??) has made it an essential part of peoples lives. The web provides enormous amount of information, however, it is very important for the users to be able to gauge the trustworthiness of web information. Users normally access content from the first few links provided to them by search engines such as Google or Yahoo!. This is assuming that these search engines provide factual information, which may be popular due to criteria such as page rank but may not always be trustworthy from the factual aspects. This paper presents a mechanism to determine trust of websites based on the semantic similarity of their multimedia content with already established and trusted websites. The proposed method allows for dynamic computation of the trust level of websites of different domains and hence overcomes the dependency on traditional user feedback methods for determining trust. In fact, our method attempts to emulate the evolving process of trust that takes place in a user??s mind. The experimental results have been provided to demonstrate the utility and practicality of the proposed method.     

基于信任网络的C2C电子商务信任算法

C2C电子商务交易具有匿名性、随机性、动态性的特点,交易双方仅通过虚拟网络交换信息,缺乏基本的信任基础,交易存在较大的风险.构造科学的信任计算模型、客观度量卖家的可信度、辅助买家(消费者)做出正确的购买决策,是降低交易风险的有效手段之一.为此,从买家的角度出发,详细讨论了信任网络的基本概念及其相关属性,并以信任的时间敏感性、不对称性、可传递性和可选择性为基础,建立了C2C电子商务环境下的动态信任算法(C2C dynamic trust algorithm,简称CDTA).该算法首先通过买家自身的交易经验计算买家对卖家的直接信任度,然后计算来自信任网络中买家的朋友对卖家的推荐信任度,最后通过信任调节因子集成直接信任度和推荐信任度来获得买家对卖家的信任度.仿真实验分析结果表明:一方面,该算法考虑了交易的多属性及其相关性,信任评价的粒度更加细化,使得信任计算的结果更加客观;另一方面,评价相似度可以很好地筛选出符合买家“个性”的推荐节点,使推荐信任度更准确,可以进一步抑制恶意节点对信任算法的影响.     

Enabling topic-level trust for collaborative information sharing

As a consequence of the exponential growth of Internet and its services, including social applications fostering collaboration on the Web, information sharing had become pervasive. This caused a crescent need of more powerful tools to help users with the task of selecting interesting resources. Recommender systems have emerged as a solution to evaluate the quality of massively user-generated contents in open environments and provide recommendations based not only on the user interests but also on the opinions of people with similar tastes. In addition to interest similarity, however, trustworthiness is a factor that recommenders have to consider in the selection of reliable peers for collaboration. Most approaches in this regard estimates trust base on global user profile similarity or history of exchanged opinions. In this paper, we propose a novel approach for agent-based recommendation in which trust is independently learned and evolved for each pair of interest topics two users have in common. Experimental results show that agents learning who to trust about certain topics reach better levels of precision than considering interest similarity exclusively.     

Applying virtual reality for trust-building e-commerce environments

The application of virtual reality in e-commerce has enormous potential for transforming online shopping into a real-world equivalent. However, the growing research interest focuses on virtual reality technology adoption for the development of e-commerce environments without addressing social and behavioral facets of online shopping such as trust. At the same time, trust is a critical success factor for e-commerce and remains an open issue as to how it can be accomplished within an online store. This paper shows that the use of virtual reality for online shopping environments offers an advanced customer experience compared to conventional web stores and enables the formation of customer trust. The paper presents a prototype virtual shopping mall environment, designed on principles derived by an empirically tested model for building trust in e-commerce. The environment is evaluated with an empirical study providing evidence and explaining that a virtual reality shopping environment would be preferred by customers over a conventional web store and would facilitate the assessment of the e-vendor’s trustworthiness.     

vCOM: Electronic commerce in a collaborative virtual world

Existing e-commerce applications on the web provide the users a relatively simple, browser-based interface to access available products. Customers are not provided with the same shopping experience as they would in an actual store or mall. This experience, however, can be achieved by the creation of a virtual shopping mall environment, simulating most of the actual shopping user interactions. The virtual mall brings together the services and products of various vendors. Users can navigate through the virtual shopping malls, adding items of interest into a virtual shopping cart, and perform searches assisted by ‘intelligent agents’. A Collaborative Virtual Environment (CVE) can realize a sophisticated virtual shopping application. In such a CVE, a large number of potential users may interact with each other. In this paper, vCOM, a VRML and Java3D-based prototype is presented, which permits users to navigate around virtual e-commerce worlds and perform collaborative shopping and intelligent searches with the assistance of software agents, in order to find the products and services of interest to them. They can then negotiate with sales agents to bargain for the best possible price and then make a secure buying transaction. The virtual mall prototype also allows the user to communicate with an ‘intelligent shopping assistant’ using simple voice commands. This assistant interacts with the shopper using voice synthesis and helps him/her use the interface to efficiently navigate in the mall. Real-time interactions between the entities in this shared environment are implemented over the High Level Architecture (HLA), an IEEE standard for distributed simulations and modeling. The paper focuses on user interface design, collaborative e-commerce through HLA and multi-agent architecture.     

Trust-inspiring explanation interfaces for recommender systems

A recommender system’s ability to establish trust with users and convince them of its recommendations, such as which camera or PC to purchase, is a crucial design factor especially for e-commerce environments. This observation led us to build a trust model for recommender agents with a focus on the agent’s trustworthiness as derived from the user’s perception of its competence and especially its ability to explain the recommended results. We present in this article new results of our work in developing design principles and algorithms for constructing explanation interfaces. We show the effectiveness of these principles via a significant-scale user study in which we compared an interface developed based on these principles with a traditional one. The new interface, called the organization interface where results are grouped according to their tradeoff properties, is shown to be significantly more effective in building user trust than the traditional approach. Users perceive it more capable and efficient in assisting them to make decisions, and they are more likely to return to the interface. We therefore recommend designers to build trust-inspiring interfaces due to their high likelihood to increase users’ intention to save cognitive effort and the intention to return to the recommender system.     

Comparative trust management with applications: Bayesian approaches emphasis

Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, and semantic sensor web. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update becomes critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and robust systems for managing trust in order to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics or computation in many situations. We motivate the trust problem, explain the relevant concepts, summarize research in modeling trust and gleaning trustworthiness, and discuss challenges confronting us. The goal is to provide a comprehensive broad overview of the trust landscape, with the nitty-gritties of a handful of approaches. We also provide details of the theoretical underpinnings and comparative analysis of Bayesian approaches to binary and multi-level trust, to automatically determine trustworthiness in a variety of reputation systems including those used in sensor networks, e-commerce, and collaborative environments. Ultimately, we need to develop expressive trust networks that can be assigned objective semantics.     

Virtual agents in retail web sites: Benefits of simulated social interaction for older users

This study investigates the benefits of simulated social interaction (social presence) through virtual agents for older users’ experience in retail Web sites, particularly with respect to age-related barriers to the adoption of online retailing. In Study 1, through four focus group interviews, we identified six social–psychological barriers to the adoption of online shopping among older users (mean age of 73 years). These included barriers relating to perceived risks, trust, social support, familiarity, experience, and search. In Study 2, a laboratory experiment with older users (mean age of 69 years) demonstrated that embedding a virtual agent that serves search and navigational/procedural support functions in the online store leads to increased perceived social support, trust, and patronage intention for the online store. Mediational analyses further revealed that the effect of virtual agents: (1) on trust is mediated by perceived social support; and (2) on patronage intentions is mediated in part by trust and perceived risks. The study provides important implications on the design of virtual agents for older users of e-commerce applications, and on building online trust and e-service patronage through virtual agents.     

The concept of decentralized and secure electronic marketplace

For commerce (electronic or traditional) to be effective, there must be a degree of trust between buyers and sellers. In traditional commerce, this kind of trust is based on such things as societal laws and customs, and on the intuition people tend to develop about each other during interpersonal interactions. The trustworthiness of these factors is based, to a large extent, on the geographical proximity between buyers and sellers. But this proximity is lost in e-commerce. In conventional electronic marketplaces the trust among participants is supported by a central server which imposes certain trading rules on all transactions. But such centralized marketplaces have serious drawbacks, among them: lack of scalability, and high cost. In this paper we propose the concept of Decentralized Electronic Marketplace (DEM) which allow buyers and sellers to engage in commercial transactions, subject to an explicitly stated set of trading rules, called the law of this marketplace—which they can trust to be observed by their trading partners. This trust is due to a decentralized, and thus scalable, mechanism that enforces the stated law of the DEM. We implement an electronic marketplace for airline tickets in order to illustrate the feasibility of the proposed concepts for decentralized and secure electronic marketplace.     

Adding security and trust to multiagent systems

Multiagent systems (MASs) are societies whose individuals are software delegatees (agents) acting on behalf of their owners or delegators (people or organizations). When deployed in an open network such as the Internet, MASs face some trust and security issues. Agents comeand go, and interact with strangers. Assumptions about security and general trustworthiness of agents and their deployers are inadequate in this context. In this paper, the design of a security infrastructure is presented applicable to MASs in general. This design addresses both security threats and trust issues. In this design, there are mechanisms for ensuring secure communication among agents and secure naming and resource location services. And two types of trusts are addressed: trust that agents will not misbehave and trust that agents are really delegatees of whom they claim to be. To establish the first type of trust, deployers of agents are made liable for the actions of their agents; to establish the second type of trust, it is proposed that agents prove that they know secrets that only their delegators know.     

Distributed Reputation Management for Electronic Commerce

One of the major challenges for electronic commerce is how to establish a relationship of trust between different parties. Establishing trust is nontrivial, because the traditional physical or social means of trust cannot apply directly in virtual settings. In many cases, the parties involved may not ever have interacted before. Reputation systems seek to address the development of trust by recording the reputations of different parties. However, most existing reputation systems are restricted to individual market websites. Further, relevant information about a party may come from several websites and from interactions that were not mediated by any website.
This paper considers the problem of automatically collecting ratings about a given party from others. Our approach involves a distributed agent architecture and adapts the mathematical theory of evidence to represent and propagate the ratings that participants give to each other. When evaluating the trustworthiness of a given party, a peer combines its local evidence (based on direct prior interactions with the party) with the testimonies of others regarding the same party. This approach satisfies certain important properties of distributed reputation management and is experimentally evaluated through simulations.     

Evaluating trustworthiness from past performances: interval-based approaches

In many multi-agent systems, especially in the field of e-commerce, the users have to decide whether they sufficiently trust an agent to achieve a certain goal. To help users to make such decisions, an increasing number of trust systems have been developed. By trust system, we mean a system that gathers information about an agent and evaluates its trustworthiness on the basis of this information. The aim of the present paper is to develop, and analyze from an axiomatic point of view, new trust systems based on intervals. More precisely, we assume that a set of grades describing the past performances of an agent is given. Then, the goal is to construct an interval that summarizes these grades. In our opinion, such an interval gives a good account of the trustworthiness of the agent. In addition, this kind of representation format overcomes certain limitations (at a certain cost) of the approaches that represent trustworthiness by a single number. We establish seven axioms that should be satisfied by a summarizing method. Next, we develop two new methods. The first one is based on the idea that certain concentrations of grades are strong enough to pull the bounds of the summarizing interval towards themselves. The second one represents data in the setting of possibility theory, and then computes lower and upper expected values. Finally, we check that our methods satisfy the axioms introduced before, which provide theoretical justifications for them.     

Making recommendations by integrating information from multiple social networks

It is becoming a common practice to use recommendation systems to serve users of web-based platforms such as social networking platforms, review web-sites, and e-commerce web-sites. Each platform produces recommendations by capturing, maintaining and analyzing data related to its users and their behavior. However, people generally use different web-based platforms for different purposes. Thus, each platform captures its own data which may reflect certain aspects related to its users. Integrating data from multiple platforms may widen the perspective of the analysis and may help in modeling users more effectively. Motivated by this, we developed a recommendation framework which integrates data collected from multiple platforms. For this purpose, we collected and anonymized datasets which contain information from several social networking and social media platforms, namely BlogCatalog, Twitter, Flickr, Facebook, YouTube and LastFm. The collected and integrated data forms a consolidated repository that may become a valuable source for researchers and practitioners. We implemented a number of recommendation methodologies to observe their performance for various cases which involve using single versus multiple features from a single source versus multiple sources. The conducted experiments have shown that using multiple features from multiple sources is expected to produce a more concrete and wider perspective of user’s behavior and preferences. This leads to improved recommendation outcome.     

Qualitative trust model with a configurable method to aggregate ordinal data

Trust models are mechanisms that allow agents to build trust without relying on a trusted central authority. Our goal was to develop a trust model that would operate with values that humans easily understand and manipulate: qualitative and ordinal values. The result is a trust model that computes trust from experiences created in interactions and from opinions obtained from third-party agents. The trust model, termed qualitative trust model (QTM), uses qualitative and ordinal values for assessing experiences, expressing opinions and estimating trust. We treat such values appropriately; we never convert them to numbers, but merely use their relative order. To aggregate a collection of such values, we propose an aggregation method that is based on comparing distributions and show some of its properties; the method can be used in other domains and can be seen as an alternative to median and similar methods. To cope with lying agents, QTM estimates trustworthiness in opinion providers with a modified version of the weighted majority algorithm, and additionally combines trustworthiness with social links between agents; such links are obtained implicitly by observing how agents provide opinions about each other. Finally, we compare QTM against a set of well-known trust models and demonstrate that it consistently performs well and on par with other quantitative models, and in many cases even outperforms them, particularly when the number of direct experiences is low.