Trust and reputation mining in professional virtual communities

Communication technologies, such as e-mail, instant messaging, discussion forums, blogs, and newsgroups connect people together, forming virtual communities. This concept is not only used for private purposes, but is also attracting attention in professional environments, allowing to consult a large group of experts. Due to the overwhelming size of such communities, various reputation mechanisms have been proposed supporting members with information about people’s trustworthiness with respect to their contributions. However, most of today’s approaches rely on manual and subjective feedback, suffering from unfair ratings, discrimination, and feedback quality variations over time. To this end, we propose a system which determines trust relationships between community members automatically and objectively by mining communication data. In contrast to other approaches which use these data directly, e.g., by applying natural language processing on log files, we follow a new approach to make contributions visible. We perform structural analysis of discussions, examine interaction patterns between members, and infer social roles expressing motivation, openness to discussions, and willingness to share data, and therefore trust

Communal Service Delivery: How Customers Benefit from Participation in Firm-hosted Virtual P3 Communities.

Firm-hosted virtual peer-to-peer problem solving (P3) communities offer a low-cost, credible, and effective means of delivering education and ongoing assistance services to customers of complex, frequently evolving products. Building upon the social constructivist view on learning and drawing from literature on the firm-customer relationship in services marketing, we distinguish between functional and social benefits received by P3 community participants and study the central role of learning in influencing these benefit perceptions. The proposed model is tested on data gathered from 2,299 active members of a P3 community hosted by a global online auction firm, and the framework’s generalizability is demonstrated using a sample of 204 members of a global B2B software firm’s P3 community. Based on the results, specific recommendations are provided to marketers interested in implementing service support programs via customer communities, and future research opportunities are explored