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Artículo

The Big-2/ROSe Model of Online Personality: Towards a Lightweight Set of Markers for Characterizing the Behavior of Social Platform Denizens

Simari, GerardoIcon ; Martinez, Maria VaninaIcon ; Gallo, Fabio RafaelIcon ; Falappa, Marcelo AlejandroIcon
Fecha de publicación: 09/2021
Editorial: Springer
Revista: Cognitive Computation
ISSN: 1866-9964
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Ciencias de la Computación

Resumen

The Big-5/OCEAN personality traits model, one of the central approaches to psychometrics, has been shown to have many applications over a variety of disciplines. In particular, correlations have been studied leading to effective characterization of people’s behavior, and the model has become notorious for its role in the Cambridge Analytica/Facebook scandal surrounding the 2016 US presidential elections. In this paper, we develop Big-2 (or ROSe, for Relationship to Others and to Self), a model via which the personality of users of online platforms can be studied using a lightweight set of markers focused on online behavior, avoiding the major data privacy pitfalls afflicting approaches based on more powerful models that characterize personal aspects of the human psyche. Evaluation of Big-2’s effectiveness is done in two parts: a quantitative evaluation on a specific prediction task and a qualitative one based on an analysis of the different ways in which the Big-2 traits can be derived from online behavior, proposing a general template to guide such efforts. Quantitative results show that our lightweight model can match or surpass the performance of Big-5 in a prediction task, while qualitative results show that it is feasible to implement the model based on the observation of basic online user behavior. Our main result is a general-purpose model that can be used to characterize the personality traits of users of online platforms in an ethical manner. Our proposed model provides a valuable tool to carry out effective and explainable analyses of online personality, avoiding the collection of unnecessary user data that would open the possibility for ethical violations.
Palabras clave: BEHAVIOR PREDICTION , COGNITIVE MODELS , ETHICAL AI , EXPLAINABILITY AND INTERPRETABILITY , MACHINE LEARNING , ONLINE PERSONALITY , PERSONALITY MODELS
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info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/174289
URL: https://link.springer.com/article/10.1007/s12559-021-09866-1
DOI: http://dx.doi.org/10.1007/s12559-021-09866-1
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Articulos(ICC)
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Citación
Simari, Gerardo; Martinez, Maria Vanina; Gallo, Fabio Rafael; Falappa, Marcelo Alejandro; The Big-2/ROSe Model of Online Personality: Towards a Lightweight Set of Markers for Characterizing the Behavior of Social Platform Denizens; Springer; Cognitive Computation; 13; 5; 9-2021; 1198-1214
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