Deception detection in online automated job interviews

Nathan W. Twyman, Steven J. Pentland, Lee Spitzley

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publicationHCI in Business, Government, and Organizations - 5th International Conference, HCIBGO 2018, Held as Part of HCI International 2018, Proceedings
EditorsBo Sophia Xiao, Fiona Fui-Hoon Nah
PublisherSpringer Verlag
Pages206-216
Number of pages11
ISBN (Print)9783319917153
DOIs
StatePublished - 2018
Event5th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2018 Held as Part of HCI International 2018 - Las Vegas, United States
Duration: 15 Jul 201820 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10923 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2018 Held as Part of HCI International 2018
Country/TerritoryUnited States
CityLas Vegas
Period15/07/1820/07/18

Keywords

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

Fingerprint

Dive into the research topics of 'Deception detection in online automated job interviews'. Together they form a unique fingerprint.

Cite this