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首页> 外文期刊>Journal of digital information management >An Adaptive Trust Metric Allowing CRM Operators to Protect Sensitive Data During Interaction in Online Social Media
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An Adaptive Trust Metric Allowing CRM Operators to Protect Sensitive Data During Interaction in Online Social Media

机译：自适应信任度量，允许CRM经营者在在线社交媒体互动期间保护敏感数据

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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.
机译：现代人越来越多地通过在线平台在当今信息驱动的社会中披露个人信息。该信息由在线平台用于特定的上下文-并可能被平台的其他合作伙伴或用户重用。当前的示例包括收集垃圾邮件的电子邮件，广告中使用的个人照片或未经明确目的同意而保留竞争对手信息。随着在线协作的兴起，信息的集成和聚合在整个在线平台上变得越来越流行，诸如无意识的信息泄露之类的隐私问题变得越来越关键。当代表公司的个人使用个人帐户与在线平台进行互动来管理企业和私人关系时，尤其如此：存在固有的风险，即敏感信息可能会无意间共享给错误的受众，从而带来不小的后果。欧洲研究项目digital.me开发了以用户为中心的信任度量，该度量为智能推荐系统提供支持，以在用户共享潜在敏感信息时向其提供隐私建议。该度量标准已在在线社交网络（OSN）演示原型di.me用户软件以及客户关系管理（CRM）演示原型di.me CRM中进行了测试，以确定该度量标准是否找到了共振操作符。快速增长的CRM市场细分。在这种情况下，针对技术接受的三种中介条件对信任度进行了验证：可用性和普遍接受，实用程序和隐私问题。涉及447位CRM操作员的现场试验表明，在OSN和CRM原型中，这三个条件均取得了积极成果。

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