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 Under a Creative Commons license Open access Highlights• A novel statement-based framework for interpretable and explainable personality prediction. •The first automated personality assessment based on the realistic accuracy model. •Supports estimation of traits on all levels of personality trait taxonomy. •Personality-indicative statements as relevant cues are abundant in social media texts. Effective framework implementation for supervised and unsupervised Big 5 estimations. AbstractAutomated text-based personality assessment (ATBPA) methods can analyze large amounts of text data and identify nuanced linguistic personality cues. However, current approaches lack the interpretability, explainability, and validity offered by standard questionnaire instruments. To address these weaknesses, we propose an approach that combines questionnaire-based and text-based approaches to personality assessment. Our Statement-to-Item Matching Personality Assessment (SIMPA) framework uses natural language processing methods to detect self-referencing descriptions of personality in a target’s text and utilizes these descriptions for personality assessment. The core of the framework is the notion of a trait-constrained semantic similarity between the target’s freely expressed statements and questionnaire items. The conceptual basis is provided by the realistic accuracy model (RAM), which describes the process of accurate personality judgments and which we extend with a feedback loop mechanism to improve the accuracy of judgments. We present a simple proof-of-concept implementation of SIMPA for ATBPA on the social media site Reddit. We show how the framework can be used directly for unsupervised estimation of a target’s Big 5 scores and indirectly to produce features for a supervised ATBPA model, demonstrating state-of-the-art results for the personality prediction task on Reddit. KeywordsText-based personality assessment Natural language processing Text analysis Social media text Realistic accuracy model Personality prediction Cited by (0)Matej Gjurković is a Ph.D. student and a research associate at the University of Zagreb, Faculty of Electrical Engineering and Computing (FER). He has been involved in several national and EU projects as a research engineer. His research interests focus on using natural language processing methods for personality prediction and analysis based on social media text. Iva Vukojević is a Ph.D. candidate in psychology at the University of Zagreb, Faculty of Humanities and Social Sciences, and a research associate at the University of Zagreb, Faculty of Electrical Engineering and Computing (FER). Her research interests revolve around exploring human behavior in a text-based digital footprint form, focused on personality analysis and prediction from social media text. Jan Šnajder received his Ph.D. in computing from the University of Zagreb, Faculty of Electrical Engineering and Computing (FER) in 2010. From 2016 he is holding the position of an associate professor at FER at the Department of Electronics, Microelectronics, Computer and Intelligent Systems. His research interests focus on natural language processing and machine learning. He has been the principal investigator of several projects funded by the Croatian Science Foundation. © 2021 The Author(s). Published by Elsevier B.V.
On the accuracy of personality judgment: a realistic approachD C Funder. Psychol Rev. 1995 Oct. AbstractThe "accuracy paradigm" for the study of personality judgment provides an important, new complement to the "error paradigm" that dominated this area of research for almost 2 decades. The present article introduces a specific approach within the accuracy paradigm called the Realistic Accuracy Model (RAM). RAM begins with the assumption that personality traits are real attributes of individuals. This assumption entails the use of a broad array of criteria for the evaluation of personality judgment and leads to a model that describes accuracy as a function of the availability, detection, and utilization of relevant behavioral cues. RAM provides a common explanation for basic moderators of accuracy, sheds light on how these moderators interact, and outlines a research agenda that includes the reintegration of the study of error with the study of accuracy. Similar articles
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What are the steps in the realistic accuracy model Ram?Realistic Accuracy Model (RAM) ... . The person being judged must do something relevant that is informative about the trait being judged.. This information must be available to the judge - the behavior must occur in a manner and place for you to observe it.. The judge must detect this information - aka notice it.. What concept does the realistic accuracy model Ram try to explain?The Realistic Accuracy Model (RAM) outlines a four-stage process necessary to achieve accurate personality judgments. Specifically, information relevant to the trait being judged has to be made available by the target, and the judge has to detect and utilize that information to make a judgment.
What is the Ram model psychology?The Realistic Accuracy Model (RAM; Funder, 1995; 1999) predicts that the availability of both more information and higher quality information will increase the probability that a personality judgment will achieve a high degree of accuracy.
What are the four moderators of accuracy?David Funder (1993, 1995) identified these four moderators of accuracy as the good judge, good target, good trait, Page 4 Realistic Accuracy Model 344 and good information. Good precedes each of the moderators to highlight the focus on the factors that make accurate judgments more likely.
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Place each definition on the corresponding component of the realistic accuracy model (ram).
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