Jamie C. Rasmussen

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Research on intelligent systems has emphasized the benefits of providing explanations along with recommendations. But can explanations lead users to make incorrect decisions? We explored this question in a controlled experimental study with 18 professional network security analysts doing an incident classification task using a prototype cybersecurity(More)
Analysts engaged in real-time monitoring of cybersecurity incidents must quickly and accurately respond to alerts generated by intrusion detection systems. We investigated two complementary approaches to improving analyst performance on this vigilance task: a graph-based visualization of correlated IDS output and defensible recommendations based on machine(More)
This paper examines the relationship between motivational design and its longitudinal effects on crowdsourcing systems. In the context of a company internal web site that crowdsources the identification of Twitter accounts owned by company employees, we designed and investigated the effects of various motivational features including individual / social(More)
The rise of social media in the enterprise has enabled new ways for employees to speak up and communicate openly with colleagues. This rich textual data can potentially be mined to better understand the opinions and sentiment of employees for the benefit of the organization. In this paper, we introduce Enterprise Social Pulse (ESP) -- a tool designed to(More)
We develop an integrated salesforce analytics application that combines enterprise data from human resources, compensation, and customer relationship management systems, produces predictive data-driven analytics insights to effectively manage organizations with many salespeople, and has an interactive visual interface that allows business users to explore(More)
We present CRAFT (Collaborative Reasoning and Analysis Framework and Toolkit), a tool for collaborative investigation, reasoning, and analysis. Analysts use CRAFT to represent their collective knowledge and reasoning via interconnected graphical models built upon a shared evolving ontology. These semantic models help connect analysts to digital information(More)
We introduce S&P360, a system to analyse and explore multidimensional, online data related to companies, their financial news, and the social impact of them. Our system combines official and crowd-sourced data sources to offer a broad perspective on the impact of financial newsregarding a set of companies. Our system is based on ABACUS [1], a(More)