{"title":"Multimodal approach for automatic recognition of machiavellianism","authors":"Zahra Nazari, Gale M. Lucas, J. Gratch","doi":"10.1109/ACII.2015.7344574","DOIUrl":null,"url":null,"abstract":"Machiavellianism, by definition, is the tendency to use other people as a tool to achieve one's own goals. Despite the large focus on the Big Five traits of personality, this anti-social trait is relatively unexplored in the computational realm. Automatically recognizing anti-social traits can have important uses across a variety of applications. In this paper, we use negotiation as a setting that provides Machiavellians with the opportunity to reveal their exploitative inclinations. We use textual, visual, acoustic, and behavioral cues to automatically predict High vs. Low Machiavellian personalities. These learned models have good accuracy when compared with other personality-recognition methods, and we provide evidence that the automatically-learned models are consistent with existing literature on this anti-social trait, giving evidence that these results can generalize to other domains.","PeriodicalId":6863,"journal":{"name":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","volume":"56 23","pages":"215-221"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Affective Computing and Intelligent Interaction (ACII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACII.2015.7344574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Machiavellianism, by definition, is the tendency to use other people as a tool to achieve one's own goals. Despite the large focus on the Big Five traits of personality, this anti-social trait is relatively unexplored in the computational realm. Automatically recognizing anti-social traits can have important uses across a variety of applications. In this paper, we use negotiation as a setting that provides Machiavellians with the opportunity to reveal their exploitative inclinations. We use textual, visual, acoustic, and behavioral cues to automatically predict High vs. Low Machiavellian personalities. These learned models have good accuracy when compared with other personality-recognition methods, and we provide evidence that the automatically-learned models are consistent with existing literature on this anti-social trait, giving evidence that these results can generalize to other domains.