Publication

Hirability in the wild: Analysis of online conversational video resumes

Résumé

Online social media is changing the personnel recruitment process. Until now, resumes were among the most widely used tools for the screening of job applicants. The advent of inexpensive sensors combined with the success of online video platforms has enabled the introduction of a new type of resume, the video resume. Video resumes can be defined as short video messages where job applicants present themselves to potential employers. Online video resumes represent an opportunity to study the formation of first impressions in an employment context at a scale never achieved before, and to our knowledge they have not been studied from a behavioral standpoint. We collected a dataset of 939 conversational English-speaking video resumes from YouTube. Annotations of demographics, skills, and first impressions were collected using the Amazon Mechanical Turk crowdsourcing platform. Basic demographics were then analyzed to understand the population using video resumes to find a job, and results showed that the population mainly consisted of young people looking for internship and junior positions. We developed a computational framework for the prediction of organizational first impressions, where the inference and nonverbal cue extraction steps were fully automated. Results demonstrated that automatically predicting first impressions up to a certain level was a feasible task, with up to 27% of the variance explained for extraversion, and up to 20% for social and communication skills.

À propos de ce résultat
Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.