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In an effort to assess the generalizability of factors that influence the disposition of knowledge sharing within organizations, this paper replicates a previous study that provided support for intrinsic motivators playing a dominant role in organizational science literature but applies it to a different community. A recent survey of 156 U.S. and Canadian(More)
Computer defense is not perfect. Each year hackers exploit hundreds of vulnerabilities in information systems even though millions of dollars are spent on information security. Firewalls, intrusion detection systems and patch management software all help to increase systems security, but they are only perimeter defenses. Once inside, a hacker can do(More)
Humans are not very good at detecting deception in normal communication. One possible remedy for improving detection accuracy is to educate people about various indicators of deception and then train them to spot these indicators when they are used in normal communication. This paper reports on one such training effort involving over 100 military officers.(More)
People are not very good at detecting deception in normal communication , and past efforts to train them to become better detectors have been mixed. This paper reports on a training study involving 177 military officers. In addition to developing and testing a training program to improve deception detection, this study also aimed to test different versions(More)
Uncovering lies (or deception) is of critical importance to many including law enforcement and security personnel. Though these people may try to use many different tactics to discover deception, previous research tells us that this cannot be accomplished successfully without aid. This manuscript reports on the promising results of a research study where(More)
Recent research has demonstrated the effectiveness of automated text-based deception detection. In this study, using a variety of data sets and common classification techniques, this has been shown to be an accurate technique. Previous results have shown the need to reduce the number of inputs to these models in order to prevent overfitting. While previous(More)