Lying on the Web: Implications for Expert Systems Redesign

Jiang, Zhengrui; Mookerjee, Vijay; Sarkar, Sumit

doi:10.1287/isre.1050.0046

Cited by 23 publications

(25 citation statements)

References 17 publications

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“…Walls et al [1992] coined the term "management support systems"which we adopt hereto refer to DSS, MIS, and EIS combined. We also include Expert Systems and KBS in this group, guided by literature which links expert systems to DSS [e.g., Remus and Kottemann 1986;Mookerjee et al 1995;Jiang et al 2005] and KBS to expert systems [e.g., Gregor and Benbasat 1999].…”

Section: Resultsmentioning

confidence: 99%

Thirty Years of IS Research: Core Artifacts and Academic Identity

Nevo

Nevo²,

Ein-Dor

2009

CAIS

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This paper puts forward an academic identity for the IS discipline which emerges out of its displayed academic artifactsnamely, papers published in two of the discipline"s major journals (Information Systems Research and MIS Quarterly) between 1977 and 2006. Our study focuses on two specific attributes of these papers: the focal IT Artifact and the IS Theme. An analysis of 1056 papers reveals an academic identity characterized by a relatively persistent focus on a small set of IT Artifacts and a similarly small set of IS Themes. The analysis suggests that our academic identity is indicated by two central and enduring intellectual cores associated with a handful of IT Artifacts and IS Themes, which have captured the attention of IS researchers over three decades. This academic identity may be described as the scientific study of the design, development, and management of information technologies, as well as their use by and impact on individuals, groups, and organizations. Of particular interest are information technologies (and their specific components) that enable communication, collaboration, and decision making. A follow up analysis of the papers published in 2007 and 2008 provides support to the central and enduring nature of our discipline"s intellectual core.

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Section: Resultsmentioning

confidence: 99%

Thirty Years of IS Research: Core Artifacts and Academic Identity

Nevo

Nevo²,

Ein-Dor

2009

CAIS

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“…If a customer who claims to have a medium income and a full-time job is actually unemployed with no stable income, then classifying the customer as low-risk can lead to financial losses. As previously mentioned, facing such lying behavior, a KM tree, built based on the KM method proposed by Jiang et al (2005), can replace the TT to serve as the "expert" at the time of consultation. The KM Tree, however, does not differentiate liars from truth-tellers, and hence leaves room for improvement.…”

Section: Accuracy-based Methodsmentioning

confidence: 99%

“…To cope with such input distortion, Jiang et al (2005) proposed two novel methods to improve the accuracy of recommendations. The first method, knowledge modification (or KM), generates a new decision tree (termed KM tree) based on experts' decision rules as well as users' lying patterns.…”

Section: Literature Reviewmentioning

confidence: 99%

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How to Deal with Liars? Designing Intelligent Rule-Based Expert Systems to Increase Accuracy or Reduce Cost

Cai

Jiang

Mookerjee

2017

INFORMS Journal on Computing

Self Cite

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Input distortion is a common problem faced by expert systems, particularly those deployed with a Web interface. In this study, we develop novel methods to distinguish liars from truth-tellers, and redesign rulebased expert systems to address such a problem. The four proposed methods are termed split tree (ST), consolidated tree (CT), value-based split tree (VST), and value-based consolidated tree (VCT), respectively. Among them, ST and CT aim to increase an expert system's accuracy of recommendations, and VST and VCT attempt to reduce the misclassification cost resulting from incorrect recommendations. We observe that ST and VST are less efficient than CT and VCT in that ST and VST always require selected attribute values to be verified, whereas CT and VCT do not require value verification under certain input scenarios. We conduct experiments to compare the performances of the four proposed methods and two existing methods, i.e., the traditional true tree (TT) method that ignores input distortion and the knowledge modification (KM) method proposed in prior research. The results show that CT and ST consistently rank first and second, respectively, in maximizing the recommendation accuracy, and VCT and VST always lead to the lowest and second lowest misclassification cost. Therefore, CT and VCT should be the methods of choice in dealing with users' lying behaviors. Furthermore, we find that KM is outperformed by not only the four proposed methods, but sometimes even by the TT method. This result further confirms the advantage necessity of differentiating liars from truth-tellers when both types of users exist in the population.

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“…Jiang et al [2005] conducted a study about document-centric deception on the Web. Although the term "noise" is used in the paper, the study actually deals with deception on the Web.…”

Section: Related Workmentioning

confidence: 99%

An Experimental Comparison of a Document Deception Detection Policy using Real and Artificial Deception

Yang¹,

Mannino

2012

J. Data and Information Quality

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Developing policies to screen documents for deception is often hampered by the cost of data collection and the inability to evaluate policy alternatives due to lack of data. To lower data collection costs and increase the amount of data, artificially generated deception data can be used, but the impact of using artificially generated deception data is not well understood. This article studies the impact of artificially generated deception on document screening policies. The deception and truth data were collected from financial aid applications, a document-centric area with limited resources for screening. Real deception was augmented with artificial data generated by noise and deception generation models. Using the real data and artificially generated data, we designed an innovative experiment with deception type and deception rate as factors, and harmonic mean and cost as outcome variables. We used two budget models (fixed and variable) typically employed by financial aid offices to measure the cost of noncompliance in financial aid applications. The analysis included an evaluation of a common policy for deception screening using both fixed and varying screening rates. The results of the experiment provided evidence of similar performance of screening policy with real and artificial deception, suggesting the possibility of using artificially generated deception to reduce the costs associated with obtaining training data.

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Lying on the Web: Implications for Expert Systems Redesign

Cited by 23 publications

References 17 publications

Thirty Years of IS Research: Core Artifacts and Academic Identity

Thirty Years of IS Research: Core Artifacts and Academic Identity

How to Deal with Liars? Designing Intelligent Rule-Based Expert Systems to Increase Accuracy or Reduce Cost

An Experimental Comparison of a Document Deception Detection Policy using Real and Artificial Deception

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