www.astesj.com 100 Personality Measurement Design for Ontology Based Platform using Social Media Text Andry Alamsyah * , Sri Widiyanesti, Rizqy Dwi Putra, Puspita Kencana Sari School of Economics and Business, Telkom University, Bandung 40257, Indonesia A R T I C L E I N F O A B S T R A C T Article history: Received: 03 March, 2020 Accepted: 22 April, 2020 Online: 03 May, 2020 Human behavior quantification is an essential part of psychological science. One of the cases is measuring human personality. Social media provide rich text, which can be beneficial as a data source to get valuable insight. Previous researches show that social media offered favorable circumstances for psychological researchers by tracking, analyzing, and predicting human character. In this research, we propose a personality measurement design to help to assess human character through linguistic usage from human digital traces. We construct our model by classifying social media text to the pre-determined personality facet from Big Five personality traits, mapping the knowledge to the ontology model, and implementing the model as a platform dictionary. Our model is based on the Indonesian language, which to the best of our knowledge is the first in the subject area. The platform is running effectively by using a well-established sorting algorithm, called the radix tree. Our objective is to support psychological science in adapting to a new technological era. Keywords: Big Five Personality Ontology Model Personality Measurement Personality Platform Social Media Radix Tree 1. Introduction The presence of advanced technologies, such as social media platforms and mobile devices, are shifting the way on how people communicate. Social media users have the freedom to upload daily routine information, exchanging messages, or even basic conversations [1]. The content created by the users is formed into digital traces. The personality of users revealed through their writing or textual content [2]. Each personality has its own charm that deserves attention over its complex arrangement. There are thoughts, hearts, and feelings that can change over time [3]. Hence, measuring human personality is a hard problem regarding the dynamic feeling's alteration. Personality measurement has become the most extensive research in the field of Psychology [4]. The legacy methodology of personality assessment performed by interview and written examination [5]. Those methods are integrated method, where an interview is conducted to validate the test result. The characteristic of legacy methodology requires fulfillment instruments, such as the physical tools and psychologists. In order to adapt to the new technological era, some alternative methodologies are developed for bringing a faster process and result. One of them is themeasurement through its natural environment or using digital traces on social media [6]. In this research, we utilize digital traces to put forward an automation personality measurement for minimizing fulfill instruments in the legacy methodology. Thus, it would significantly reduce the cost and reduce the time process of getting the results. This approach needs to be developed, considering that automation is the most demanded characteristic of the Industry 4.0 era. According to Madden et al. [7], digital traces, which consist of user information, e.g., personal information, shared texts, pictures, and videos, are a proof dataset that cannot be ignored, which expressed online human activity. These footprints are offered valuable opportunities for psychology research in understanding human characteristics [8]. Previous researches have assessed human personality through social media, such as Bhardwaj et al. [9], who assess personality through Facebook and LinkedIn and Park et al. [6] who applying the regression model to predict human character based on social media language. Most of the research generally uses a machine learning approach, in contrast to our study, which utilizing the ontology approach. Machine learning provides us some leverage, such as the speed of analysis regarding large-scale data [10]. It is also able to predict personality on various forms of data like text, speech, and image [11]. However, the machine learning approach has some weaknesses in processing each meaning and intention of words due to language uniqueness [12]. Ontology afford us a better understanding of contextual knowledge [13]. There is an opportunity to use ontology as a basis for measuring human personality through the words on linguistic usage. Thus, in terms of measuring human nature through social media textual data, the ASTESJ ISSN: 2415-6698 * Andry Alamsyah, Email : andrya@telkomuniversity.ac.id Advances in Science, Technology and Engineering Systems Journal Vol. 5, No. 3, 100-107 (2020) www.astesj.com Special Issue on Multidisciplinary Innovation in Engineering Science & Technology https://dx.doi.org/10.25046/aj050313