An Adaptive Trust Metric Allowing CRM Operators to Protect Sensitive Data During Interaction in Online Social Media
Sophie Wrobel, Marcel Heupel, Simon Thiel
Journal of Digital Information Management, Vol. 12, No. 1, 2014.
DOI: 
Link: http://dline.info/fpaper/jdim/v12i1/8.pdf
Abstract:
Modern individuals increasingly disclose personal information in today's information-driven society through online platforms. This information is used by the online platform for a particular context and may be reused by other partners or users of the platform in ways that may not have been intended. Current examples include email harvesting for spam, personal photographs used in advertising, or maintaining competitor information without explicit purposed consent. With integration and aggregation of information becoming increasingly popular across online platforms through the rise of online collaboration, privacy issues such as unintentional information disclosure become increasingly critical. This is particularly true where individuals representing corporations interact with online platforms using personal accounts to manage both business and private relationships: there is an inherent risk that sensitive information could be inadvertently shared to the wrong audience, with non-trivial consequences. The European research project digital.me developed a user-centric trust metric that powers an intelligent recommendation system to provide privacy advisories to users when they share potentially sensitive information. This metric was tested in an online social networking (OSN) demonstration prototype, the di.me userware, as well as in a customer relationship management (CRM) demonstration prototype, di.me CRM, to determine whether the metric found resonance operators in the rapidly growing CRM market segment. In this context, the trust metric was validated against three mediating conditions for technology acceptance: usability and general acceptance, utility, and privacy concerns. Field trials involving 447 CRM operators showed positive results for all three conditions in both OSN and CRM prototypes.