Related Experiment Video
Updated: Sep 20, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
It's Only a Small Lie: Forgivability of LinkedIn Fraud
Eryn A Nielsen1, Dalia L Diab2
1Human Resources Research Organization (HumRRO), Louisville, KY, USA.
Abstract:
LinkedIn has become a more prevalent recruitment and selection tool for employers. However, two issues that could potentially arise in the usage of LinkedIn in the hiring process are fraud and racial discrimination. The purpose of this study, therefore, was to examine the effect of type of LinkedIn fraud (embellishment vs. fabrication) on ratings of forgivability and hireability based on an applicant's race (Black vs. White). Using a 2 x 2 between-subjects factorial design, 179 participants recruited from Prolific were randomly assigned to one of four hypothetical LinkedIn profiles: Black applicant with an embellished LinkedIn profile, Black applicant with a fabricated LinkedIn profile, White applicant with an embellished LinkedIn profile, or White applicant with a fabricated LinkedIn profile. After reviewing the profile, participants were asked to rate their likelihood of hiring the applicant and forgiving them for committing fraud. Results revealed that the main effect of type of fraud was significant, such that it was significantly more likely for participants to forgive and hire an applicant if they embellished rather than fabricated their LinkedIn profile. Therefore, it was easier to excuse a less harsh lie. However, the current study did not find evidence of an interaction between applicant race and type of fraud committed on either forgivability or hireability, suggesting that no racial discrimination was detected in this study. Tendency to forgive and religiosity were also included as covariates in further analyses, but neither changed the pattern of results. These findings suggest that forgiveness and hiring decisions may not be based on who committed the lie, but the nature of the lie itself.
Related Concept Videos
Impression Management Techniques III: Aligning Actions
Understanding Deception
Fundamental Attribution Error
Bullying
Ligand Binding and Linkage
Types of Errors: Detection and Minimization
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...

