Title

Deception Detection in Online Automated Job Interviews

Abstract

This research-in-progress paper presents a conceptual system for automated deception detection in online interviewing. The design proposes video recordings of responses to predefined, structured interview question sets variously selected based on the desired behavioral metric of interest, such as competence, social skills, or in this case, veracity. Raw behavioral data extracted from video responses is refined to produce indicators of behavioral metrics. A prototype implementation of the design was built and tested experimentally using a job interview scenario. Results of the experimental analysis provide evidence of the potential of the concept.

Meeting Name

5th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2018 (2018: Jul. 15-20, Las Vegas, NV)

Department(s)

Business and Information Technology

Keywords and Phrases

Automated interviewing; Behavioral assessment; Deception detection; Human risk assessment; Virtual agent-based interviewing

International Standard Book Number (ISBN)

978-331991715-3

International Standard Serial Number (ISSN)

0302-9743

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Springer Verlag, All rights reserved.

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