Person to person trust factors in word of mouth recommendation

Online recommender systems and review sites do not currently reflect how people seek information using social networks of people they know. Developing systems that overcome this limitation requires studies of how people choose sources for recommendations and assess their trustworthiness. This paper presents the findings of such a study and discusses their implications for search and recommender applications

Bridging the gap between human and machine trust : applying methods of user-centred design and usability to computer security

This work presents methods for improving the usability of security. The work focuses on trust as part of computer security. Methods of usability and user-centred design present an essential starting point for the research. The work uses the methods these fields provide to investigate differences between machine and human trust, as well as how the technical expressions of trust could be made more usable by applying these methods. The thesis is based on nine publications, which present various possibilities to research trust with user-centric methods. The publications proceed chronologically and logically from the first user interviews about trust, trusting attitudes and behaviours in general to the actual design and usability testing of user interfaces for security applications, finally presenting the outcomes and conclusions of the research. The work also presents a review of relevant previous work in the area, concentrating on work done in the fields of usability and user-centred design. The work is of cross-disciplinary nature, falling into the areas of human-computer interaction, computer science and telecommunications. The ultimate goal of the conducted research has been to find out 1) how trust is to be understood in this context; 2) what methods can be used to gain insight into trust thus defined; and, finally, 3) what means can be used to create trust in the end users in online situations, where trust is needed. The work aims at providing insight into how trust can be studied with the methods provided by user-centred design and usability. Further, it investigates how to take understanding of trust formation in humans into account when attempting to design trust-inducing systems and applications. The work includes an analysis and comparison of the methods used: what kinds of methods to study trust exist in the field of usability and user-centred design. Further, it is evaluated, what kind of results and when can be reached with the different methods available, by applying a variety of these methods. Recommendations for the appropriate application of these methods when studying the various parts of trust is one of the outcomes. The results received with the methods used have also been compared with results received by others by applying alternative methods to the same research questions. On a conceptual level, the work contains an analysis of the concept of trust. It also contains a brief investigation into both technical and humane ways to express trust, with a comparison between the two

Information-seeking on the Web with Trusted Social Networks - from Theory to Systems

This research investigates how synergies between the Web and social networks can enhance the process of obtaining relevant and trustworthy information. A review of literature on personalised search, social search, recommender systems, social networks and trust propagation reveals limitations of existing technology in areas such as relevance, collaboration, task-adaptivity and trust. In response to these limitations I present a Web-based approach to information-seeking using social networks. This approach takes a source-centric perspective on the information-seeking process, aiming to identify trustworthy sources of relevant information from within the user's social network. An empirical study of source-selection decisions in information- and recommendation-seeking identified five factors that influence the choice of source, and its perceived trustworthiness. The priority given to each of these factors was found to vary according to the criticality and subjectivity of the task. A series of algorithms have been developed that operationalise three of these factors (expertise, experience, affinity) and generate from various data sources a number of trust metrics for use in social network-based information seeking. The most significant of these data sources is Revyu.com, a reviewing and rating Web site implemented as part of this research, that takes input from regular users and makes it available on the Semantic Web for easy re-use by the implemented algorithms. Output of the algorithms is used in Hoonoh.com, a Semantic Web-based system that has been developed to support users in identifying relevant and trustworthy information sources within their social networks. Evaluation of this system's ability to predict source selections showed more promising results for the experience factor than for expertise or affinity. This may be attributed to the greater demands these two factors place in terms of input data. Limitations of the work and opportunities for future research are discussed