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Journal articles on the topic 'Personality Computing'

Author: Grafiati

Published: 11 March 2023

Last updated: 31 July 2025

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1

Vinciarelli, Alessandro, and Gelareh Mohammadi. "More Personality in Personality Computing." IEEE Transactions on Affective Computing 5, no. 3 (2014): 297–300. http://dx.doi.org/10.1109/taffc.2014.2341252.

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Vinciarelli, Alessandro, and Gelareh Mohammadi. "A Survey of Personality Computing." IEEE Transactions on Affective Computing 5, no. 3 (2014): 273–91. http://dx.doi.org/10.1109/taffc.2014.2330816.

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Johnson, Richard D., Natasha Veltri, and Jason B. Thatcher. "Beliefs and Attributions toward Computing Technology." Journal of Organizational and End User Computing 27, no. 3 (2015): 27–54. http://dx.doi.org/10.4018/joeuc.2015070102.

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This study critiques and extends the work of , who investigated the relations between social cues in an interface, user personality, user beliefs about the social role and capabilities of computers, and the attributions of responsibility users made for their interactions and outcomes with a computer. In this study, rather than examining the simple, direct effects investigated previously, we examine the moderating role of social cues in the interface. In addition, building upon recent findings from psychology, the authors assess personality traits individually, rather than aggregating them. To

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Mahamad Amin, Nurrul Akma, Nilam Nur Amir Sjarif, and Siti Sophiayati Yuhaniz. "A Review of Convolutional Neural Network Model for Audio-Visual Features Extraction in Personality Traits Recognition." International Journal of Innovative Computing 15, no. 1 (2025): 45–52. https://doi.org/10.11113/ijic.v15n1.498.

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In the field of personality computing research, the analysis on audio-visual input is predominantly used to detect human personality behaviors. With the advancement of computer vision technology, there has been significant enhancement in personality computing. Personality trait recognition is one of the applications under personality computing where the machine can analyze human behaviors and recognize personality traits via video analysis. In video input, there are different audio-visual features characteristics, consisting of visual (images) and audio (sounds) elements. Therefore, it is crit

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Chuanqin, Zheng. "Computing Personality Trait Based on Multi-source." Journal of Physics: Conference Series 1955, no. 1 (2021): 012100. http://dx.doi.org/10.1088/1742-6596/1955/1/012100.

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Wisnubroto, Petrus. "PENGARUH FAKTOR DEMOGRAFI DAN PERSONALITY TERHADAP KEAHLIAN DALAM END USER COMPUTING (Studi Kasus Guru dan Karyawan Administrasi pada Sekolah Menengah Atas Negeri di Kotamadya Yogyakarta)." Conference SENATIK STT Adisutjipto Yogyakarta 1 (December 3, 2013): 1. http://dx.doi.org/10.28989/senatik.v1i0.54.

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This study aims to analyze the influence of demographic factors ( age , gender , education , experience ) and personality factors ( computer anxiety , computer attitude , math anxiety ) to the end user computing expertise of personnel either partially or simultaneously . Models the influence of the demographic variables and personality skills in end user computing research model replicated from Harrison and Rainer (1992 ) and the research model and Gudono Rifa (1998). The study was conducted on teacher and administrative employees of State High School I to XI in Yogyakarta Municipality conside

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Nunes, Maria Augusta Silveira Netto. "Psychological Aspects in lifelike synthetic agents: Towards to the Personality Markup Language (A Brief Survey)." RENOTE 7, no. 3 (2009): 390–400. http://dx.doi.org/10.22456/1679-1916.13581.

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This paper describes how human psychological aspects have been used in lifelike synthetic agents in order to provide believability during the human-computer interaction. We describe a brief survey of applications where Affective Computing Scientists have applied psychological aspects, like Emotion and Personality. Based on those aspects we describe the effort done by Affective Computing scientists in order to create a Markup Language to express and standardize Emotions. Because they have not yet concentrated their effort on Personality, here, we propose a starting point to create a Markup Lang

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Mahamad Amin, Nurrul Akma, Nilam Nur Amir Sjarif, and Siti Sophiayati Yuhaniz. "Convolutional Neural Network Model for Facial Feature Extraction in Personality Traits Recognition." Open International Journal of Informatics 11, no. 2 (2023): 133–40. http://dx.doi.org/10.11113/oiji2023.11n2.281.

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Personality computing lies on the effort of designing computational models to recognize personality traits from different sources of input such as visual (image), verbal (text) and vocal (audio). To recognize personality traits from facial images, the recognition model needs to extract facial features such as eyes, mouth, nose, etc. Facial features are relevant for personality judgements where they are providing information about human expression and behaviours. For example, by detecting eye’s movement, dimension and size, machines can describe people’s personality. Basically, people with high

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Yang, Guo Liang, Jin Hui Zhang, and Hui Sun. "Design of Emotional Interaction System Based on Affective Computing Model." Applied Mechanics and Materials 198-199 (September 2012): 367–73. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.367.

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An emotional interaction system is designed by using the theories about affective computing in this paper, which includes the emotional information capturing, machine emotional model and emotional expression. This paper focuses on the problem of building machine emotional model, not only gives the basic definitions of personality space, mood space, and emotion space, but also establishes the quantitative relationship of personality mood and emotion. At last, this paper builds a machine affective model which can reflect the transformation law of the mood, emotion and personality. Related simula

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Bhushan, Shashi. "An Efficient Soft Computing Approach for Text Identification using Artificial Intelligence Model." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 3860–66. http://dx.doi.org/10.22214/ijraset.2021.35766.

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This paper presents an enhanced system in the field of text identification using Soft computing techniques. The model designed in this work analyzes the blogs or input text and classifies the personality into five major categories; Neuroticism, Extraversion, Openness, Conscientiousness and Agreeableness. The blog or text is first passed through POS tagger then a feature vector matrix is generated according to the attributes of the personality chart. Each column of FVM is calculated in its domain that improves the final result of personality identification. The result of the proposed model is i

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Omheni, Nizar, Anis Kalboussi, Omar Mazhoud, and Ahmed Hadj Kacem. "Computing of Learner’s Personality Traits Based on Digital Annotations." International Journal of Artificial Intelligence in Education 27, no. 2 (2016): 241–67. http://dx.doi.org/10.1007/s40593-016-0124-x.

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Choong, En Jun, and Kasturi Dewi Varathan. "Predicting judging-perceiving of Myers-Briggs Type Indicator (MBTI) in online social forum." PeerJ 9 (June 23, 2021): e11382. http://dx.doi.org/10.7717/peerj.11382.

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The Myers-Briggs Type Indicator (MBTI) is a well-known personality test that assigns a personality type to a user by using four traits dichotomies. For many years, people have used MBTI as an instrument to develop self-awareness and to guide their personal decisions. Previous researches have good successes in predicting Extraversion-Introversion (E/I), Sensing-Intuition (S/N) and Thinking-Feeling (T/F) dichotomies from textual data but struggled to do so with Judging-Perceiving (J/P) dichotomy. J/P dichotomy in MBTI is a non-separable part of MBTI that have significant inference on human behav

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Stoliarova, Valeriia, Fedor Bushmelev, and Maxim Abramov. "Associations between the Avatar Characteristics and Psychometric Test Results of VK Social Media Users." Mathematics 11, no. 20 (2023): 4300. http://dx.doi.org/10.3390/math11204300.

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Online social media has an increasing influence on people’s lives, providing tools for communication and self–representation. People’s digital traces are gaining attention as a reflection of their personality traits, enhancing the personality computing tasks in various areas. This study aims at the identification of statistical associations between psychometric scores from three questionnaires—the Big Five Inventory, Plutchik’s Lifestyle Index and the Eysenck Personality Questionnaire—and a set of graphical features of avatar images from the VK online social media that include the pixel charac

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Ryumina, E. V., and A. A. Karpov. "IMPACT OF VISUAL MODALITIES IN MULTIMODAL PERSONALITY AND AFFECTIVE COMPUTING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-2/W3-2023 (May 12, 2023): 217–24. http://dx.doi.org/10.5194/isprs-archives-xlviii-2-w3-2023-217-2023.

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Abstract. Personality and affective computing techniques play a significant role for better understanding of human’s behavior and intentions. Such techniques can be applied in practice in recommendation systems, healthcare, education, and job applicant screening. In this paper, we propose a novel multimodal approach to personality traits assessment that leverages affective features of human’s voice and face, as well as recent advances in the deep learning. We present a new mid-level modality fusion strategy that is based on a cross-modal attention mechanism with summarizing functionals. In con

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Board, Editorial. "Well-known Personality in a Technical World and Information System." Global Journal of Enterprise Information System 8, no. 1 (2016): 62. http://dx.doi.org/10.18311/gjeis/2016/7294.

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We are pleased to share profile of Col. Inderjit Singh (Retd). Inderjit is a an experienced Information Systems and Information Security Professional with experience of more than 25 year across a wide spectrum of areas spanning Solution Architecture, Program/Project Management Telecom, IT Infrastructure Management, Info Security Advisory and Architecture, Cyber Security, Cyber Warfare and Cyber Forensics, Data Centers Design and Operations, Cloud Computing and E-Commerce Startup. An experienced Information Systems Professional with experience of more than 25 year across a wide spectrum of area

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Kiciman, Emre. "Workshops." Proceedings of the International AAAI Conference on Web and Social Media 7, no. 1 (2021): xxv—xxvi. http://dx.doi.org/10.1609/icwsm.v7i1.14376.

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The workshops presented at ICWSM 2013 included Computational Personality Recognition (Shared Task), Social Computing for Workforce 2.0, Social Media Visualization, and When The City Meets The Citizen.

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Rajput, K. R. "Multimodal Intelligence in Recruitment: Modelling Personality and Behavioural Traits from Video Interviews." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 5199–205. https://doi.org/10.22214/ijraset.2025.71416.

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With advances in AI and deep learning, automated personality analysis from video interviews has emerged as a key area in personality computing and psychological assessment. Leveraging computer vision and pattern recognition, modern models now interpret nonverbal cues to estimate personality traits directly from visual input. The recruitment landscape often depends on manual assessments that are susceptible to bias and inconsistency, making objective candidate evaluation challenging. While asynchronous video interviews (AVIs) offer scalability and convenience, they still fall short in capturing

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Das, Aditi. "Automatic Personality Identification using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 3528–34. http://dx.doi.org/10.22214/ijraset.2021.35386.

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Machine Learning has made significant changes in the world making our life more easier and comfortable .One of the most exciting applications is the prediction of Personality automatically using different algorithms. Personality computing and emotive computing, where the popularity of temperament traits is important, have gained increasing interest and a spotlight in several analysis areas recently. These applications can powerfully predict the personality of a Person. The aim of this paper is to use a more rigorous construct Validation system to extend the potential of machine learning approa

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Xu, Jia, Weijian Tian, Guoyun Lv, Shiya Liu, and Yangyu Fan. "2.5D Facial Personality Prediction Based on Deep Learning." Journal of Advanced Transportation 2021 (June 30, 2021): 1–12. http://dx.doi.org/10.1155/2021/5581984.

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The assessment of personality traits is now a key part of many important social activities, such as job hunting, accident prevention in transportation, disease treatment, policing, and interpersonal interactions. In a previous study, we predicted personality based on positive images of college students. Although this method achieved a high accuracy, the reliance on positive images alone results in the loss of much personality-related information. Our new findings show that using real-life 2.5D static facial contour images, it is possible to make statistically significant predictions about a wi

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Vukojicic, Milic, and Mladen Veinovic. "Trait analysis based on multimodal prediction and optimization of the output parameters: A survey." Serbian Journal of Electrical Engineering 20, no. 2 (2023): 229–42. http://dx.doi.org/10.2298/sjee2302229v.

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This paper provides a survey of apparent personality trait analysis based on multimodal trait prediction and optimization of multimodal output parameters. This paper analyzes, synthesizes, and compares the development of different methods of Personality computing based on the personality trait analysis within the Big Five model (OCEAN model) and based on audio, visual and textual inputs. The results of the trait analysis and detection are different for different methods, from trait extracted from handwriting with an accuracy of 62-83%, trait extracted from with 56-62%, trait extracted from aud

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Kumar Yadav, Santosh, Shiv Prakash, and Rajat Kumar Jain. "TRI-GUNAS (SATTVA, RAJAS AND TAMAS) AND RISK-TAKING BEHAVIOR AMONG UNDERGRADUATE STUDENTS." International Journal of Research -GRANTHAALAYAH 4, no. 1 (2016): 138–45. http://dx.doi.org/10.29121/granthaalayah.v4.i1.2016.2852.

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Tri-Gunas is considered an important personality factors in the eastern philosophy. Objective of the present study is to find out co-relation between Tri-Gunas factors of personality and risk- taking behavior among undergraduate students. Sample consists of 192 under graduate students (94 male & 98 female) selected by adopting random sampling method. The tools used for the study are Personality Assessment Profile by Dr. UpendraDhar, Dr. SapanaParashar and Dr. Santosh Dhar and Risk taking Questionnaire constructed by Verendra Sinha and P.N. Arora. Statistical analysis was done by comp

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Santosh, Kumar Yadav, Prakash Shiv, and Kumar Jain Rajat. "TRI-GUNAS (SATTVA, RAJAS AND TAMAS) AND RISK-TAKING BEHAVIOR AMONG UNDERGRADUATE STUDENTS." International Journal of Research – Granthaalayah 4, no. 1 (2017): 138–45. https://doi.org/10.5281/zenodo.848513.

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Tri-Gunas is considered an important personality factors in the eastern philosophy. Objective of the present study is to find out co-relation between Tri-Gunas factors of personality and risk- taking behavior among undergraduate students. Sample consists of 192 under graduate students (94 male & 98 female) selected by adopting random sampling method. The tools used for the study are Personality Assessment Profile by Dr. Upendra Dhar, Dr. Sapana Parashar and Dr. Santosh Dhar and Risk taking Questionnaire constructed by Verendra Sinha and P.N. Arora. Statistical analysis was done by computin

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Bhaskar, Riya. "Survey on Personality Detection on Multilingual Dataset using Machine Learning and Explainable AI." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 6930–40. https://doi.org/10.22214/ijraset.2025.71767.

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Abstract: Personality detection is a key area in AI, significantly impacting psychological profiling, behavioral analysis, and personalized recommendations. It addresses the new frontiers of multilingual personality detection using machine learning (ML) and Explainable AI (XAI). In this review paper, we studied the state-of-art research on deep learning and ensemble methods, while also highlighting the contributions of XAI frameworks like SHAP and LIME in improving model interpretation. We analyzed based metrics on use cases with fair and transparent measures to assess how ML methods generaliz

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G.C. Wright, Aidan. "Current Directions in Personality Science and the Potential for Advances through Computing." IEEE Transactions on Affective Computing 5, no. 3 (2014): 292–96. http://dx.doi.org/10.1109/taffc.2014.2332331.

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Carducci, Giulio, Giuseppe Rizzo, Diego Monti, Enrico Palumbo, and Maurizio Morisio. "TwitPersonality: Computing Personality Traits from Tweets Using Word Embeddings and Supervised Learning." Information 9, no. 5 (2018): 127. http://dx.doi.org/10.3390/info9050127.

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Salgado, Luciana C. C., Mirella M. Moro, Aleteia Araujo, et al. "WIT comes of Age: The Successful Story of the Women in Information Technology Workshop." Journal of the Brazilian Computer Society 31, no. 1 (2025): 36–49. https://doi.org/10.5753/jbcs.2025.4506.

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Having more women in Computing, Information Technology, and Hard Sciences is a pressing matter that has been around for at least three decades. This article presents a success story about WIT (Women in Information Technology), an event part of the CSBC (Brazilian Computer Society Congress). It was created 18 years ago as an open space to discuss gender equity issues in Computing and is currently organized by Programa Meninas Digitais – PMD (Digital Girls Program). In this article, we present the impact of WIT within the Brazilian Computing community. Quantitative and qualitative analyses were

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J Sterling, Sabrina. "The Correlation between Temperament, Technology Preference and Proficiency in Middle School Students." Journal of Information Technology Education: Research 15 (2016): 001–18. http://dx.doi.org/10.28945/2333.

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This study examined the relationship between middle school students’ personality type and their academic performance in the technology courses in which they participated. It also explored the differences in technology use by personality. Most participants identified games as a favorite pastime. However, there were some noted temperamental differences. Students with the analytical personality reported the most varied use of computers, and rated their technology skills significantly higher on the self-perception scales and performed at a higher proficiency level than their peers. The study also

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Rume, Elizabeth Yoro, Obukohwo Aghware Fidelis, Ifeanyi Akazue Maureen, Egu Ibor Ayei, and Adimabua Ojugo Arnold. "Evidence of personality traits on phishing attack menace among selected university undergraduates in Nigerian." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 1943–53. https://doi.org/10.11591/ijece.v13i2.pp1943-1953.

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Access ease, mobility, portability, and improved speed have continued to ease the adoption of computing devices; while, consequently proliferating phishing attacks. These, in turn, have created mixed feelings in increased adoption and nosedived users’ trust level of devices. The study recruited 480-students, who were exposed to socially-engineered attack directives. Attacks were designed to retrieve personal data and entice participants to access compromised links. We sought to determine the risks of cybercrimes among the undergraduates in selected Nigerian universities, observe students

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Maulidah, Mawadatul, and Hilman Ferdinandus Pardede. "Prediction Of Myers-Briggs Type Indicator Personality Using Long Short-Term Memory." Jurnal Elektronika dan Telekomunikasi 21, no. 2 (2021): 104. http://dx.doi.org/10.14203/jet.v21.104-111.

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Personality is defined as the mix of features and qualities that make up an individual's particular character, including thoughts, feelings, and behaviors. With the rapid development of technology, personality computing is becoming a popular research field by providing users with personalization. Many researchers have used social media data to automatically predict personality. This research uses a public dataset from Kaggle, namely the Myers-Briggs Personality Type Dataset. The purpose of this study is to predict the accuracy and F1-score values so that the performance for predicting and clas

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Yoro, Rume Elizabeth, Fidelis ObukohwoAghware, Maureen Ifeanyi Akazue, Ayei Egu Ibor, and Arnold Adimabua Ojugo. "Evidence of personality traits on phishing attack menace among selected university undergraduates in Nigerian." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (2023): 1943. http://dx.doi.org/10.11591/ijece.v13i2.pp1943-1953.

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Access ease, mobility, portability, and improved speed have continued to ease the adoption of computing devices; while, consequently proliferating phishing attacks. These, in turn, have created mixed feelings in increased adoption and nosedived users’ trust level of devices. The study recruited 480-students, who were exposed to socially-engineered attack directives. Attacks were designed to retrieve personal data and entice participants to access compromised links. We sought to determine the risks of cybercrimes among the undergraduates in selected Nigerian universities, observe students’ resp

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Žampachová, Barbora, Eva Landová, and Daniel Frynta. "Methods for measuring mammalian personalities: In which animals and how accurately can we quantify it?" Lynx, new series 48, no. 1 (2017): 183–98. http://dx.doi.org/10.2478/lynx-2017-0011.

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Abstract The study of personality, and individual differences in behaviour has experienced a steady rise in popularity in the past years. In this review and meta-analysis, we aim to introduce the concept of personality and related phenomena. A behavioural trait should meet two basic conditions to be considered a personality trait – it should be consistent (1) in time and (2) across contexts. In mammals, the two most common orders in personality studies are primates and rodents. We therefore introduce different approaches to personality testing in these two orders. Primate personality studies a

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Priyanka Gupta. "Multimodal Personality Prediction Improving HEXACO Trait Classification Using Adaptive Attention and Deep Feature Pruning." Journal of Information Systems Engineering and Management 10, no. 3 (2025): 748–64. https://doi.org/10.52783/jisem.v10i3.6187.

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Personality prediction has gained significant attention in affective computing, particularly in applications such as recruitment, psychological assessments, and social media profiling. Traditional personality classification methods rely on psychometric tests, which are often subjective and time-consuming. Recent advancements in deep learning have enabled automated personality assessment using facial, speech patterns and behavioral cues. However, existing models struggle with feature redundancy and computational inefficiencies, leading to suboptimal classification performance. To address these

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Guo, Ao, and Jianhua Ma. "Archetype-Based Modeling of Persona for Comprehensive Personality Computing from Personal Big Data." Sensors 18, no. 3 (2018): 684. http://dx.doi.org/10.3390/s18030684.

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Lee, Seo-young, Gyuho Lee, Soomin Kim, and Joonhwan Lee. "Expressing Personalities of Conversational Agents through Visual and Verbal Feedback." Electronics 8, no. 7 (2019): 794. http://dx.doi.org/10.3390/electronics8070794.

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As the uses of conversational agents increase, the affective and social abilities of agents become important with their functional abilities. Agents that lack affective abilities could frustrate users during interaction. This study applied personality to implement the natural feedback of conversational agents referring to the concept of affective computing. Two types of feedback were used to express conversational agents’ personality: (1) visual feedback and (2) verbal cues. For visual feedback, participants (N = 45) watched visual feedback with different colors and motions. For verbal cues, p

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Fu, Xiaomeng, Suyan Cheng, Li Zhao, and Jiaguo Lv. "Retweet Prediction Based on Multidimensional Features." Wireless Communications and Mobile Computing 2022 (February 16, 2022): 1–8. http://dx.doi.org/10.1155/2022/1863568.

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With the wide use of artificial intelligence-driven mobile devices, more and more Chinese people take part in the Twitter-like social sites, which makes Weibo an excellent communication platform. In view of the wide application of information diffusion in various fields, Weibo has become one of the most important research issues in mobile social computing. In Weibo, the retweet statuses of tweets of other users are considered to be the key mechanism for spreading information. How to predict whether a tweet will be retweeted by a user has received increasing attention in recent years. Research

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Klinkert, Lawrence J., Steph Buongiorno, and Corey Clark. "Evaluating the Efficacy of LLMs to Emulate Realistic Human Personalities." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 20, no. 1 (2024): 65–75. http://dx.doi.org/10.1609/aiide.v20i1.31867.

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To enhance immersion and engagement in video games, the design of Affective Non-Player Characters (NPCs) is a key focus for researchers and practitioners. Affective Computing frameworks improve Non-player characters (NPC) by providing personalities, emotions, and social relations. Large Language Models (LLMs) bring the promise to dynamically enhance character design when coupled with these frameworks, but further research is needed to validate the models truly represent human qualities. In this research, a comprehensive analysis investigates the capabilities of LLMs to generate content that al

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Mansi, Bosamia, and Patel Atul. "AN OVERVIEW OF CLOUD COMPUTING FOR E-LEARNING WITH ITS KEY BENEFITS." International Journal of Information Sciences and Techniques (IJIST) 6, no. 1/2 (2016): 01–10. https://doi.org/10.5281/zenodo.7278708.

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Education is a necessary human virtue and essential for society because it reflects the personality of the human being in our society. The effective way of teaching gives the quality of education and advance learning such as e-learning to the learners and also a high quality of teaching to the tutors. Information Technology (IT) plays a significant role in field of education. Now days, E-learning and M-learning have become very popular trends of the education technology riot. E-Learning is the new tool related to the virtualized distance learning by means of electronic communication mechanisms

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Gjoreski, Martin, Tine Kolenik, Timotej Knez, et al. "Datasets for Cognitive Load Inference Using Wearable Sensors and Psychological Traits." Applied Sciences 10, no. 11 (2020): 3843. http://dx.doi.org/10.3390/app10113843.

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This study introduces two datasets for multimodal research on cognitive load inference and personality traits. Different to other datasets in Affective Computing, which disregard participants’ personality traits or focus only on emotions, stress, or cognitive load from one specific task, the participants in our experiments performed seven different tasks in total. In the first dataset, 23 participants played a varying difficulty (easy, medium, and hard) game on a smartphone. In the second dataset, 23 participants performed six psychological tasks on a PC, again with varying difficulty. In both

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Archambault, Daniel, Fabio Celli, Elizabeth M. Daly, et al. "Reports on the 2013 Workshop Program of the Seventh International AAAI Conference on Weblogs and Social Media." AI Magazine 34, no. 4 (2013): 116–18. http://dx.doi.org/10.1609/aimag.v34i4.2507.

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The Workshop Program of the Program of the Seventh International AAAI Conference on Weblogs and Social Media was held July 11, 2013, in Cambridge, Massachusetts. The program included four workshops, Computational Personality Recognition (Shared Task) (WS-13-01), Social Computing for Workforce 2.0 (WS-13-02), Social Media Visualization 2 (WS-13-03), and When the City Meets the Citizen (WS-13-04). This report summarizes the activities of the four workshops.

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Chraibi, Khaoula, Ilham Chaker, Younes Dhassi, and Azeddine Zahi. "MSAPersonality: a modern standard Arabic dataset for personality recognition." MSAPersonality: a modern standard Arabic dataset for personality recognition 14, no. 4 (2024): 4498–507. https://doi.org/10.11591/ijece.v14i4.pp4498-4507.

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Automatic personality recognition is a task that attempts to automatically infer personality traits from a variety of data sources, including Text. Our words, whether spoken or written, reveal a lot about who we are. As people speak different languages, each with its own set of characteristics and level of complexity, identifying their personalities automatically might be language-dependent. This task requires an annotated text corpus with personality traits. However, the lack of corpora for languages other than English makes the task extremely challenging. W

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Wan, Chuan, and Yan Tao Tian. "Emotional Expression System Based on Expression Intensity Recognition and Affective Model." Applied Mechanics and Materials 461 (November 2013): 618–22. http://dx.doi.org/10.4028/www.scientific.net/amm.461.618.

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Affective computing is an indispensable aspect in harmonious human-computer interaction and artificial intelligence. Making computers have the ability of generating emotions is a challenging task of affective computing. Affective Computing and Artificial Psychology are new research fields that involve computer and emotions, they have the same key research aspect, affective modeling. The paper introduces the basic affective elements, and the representation of affections in a computer. And we will describe an emotion generation model for a multimodal virtual human. The relationship among the emo

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D’Mello, Sidney K., Louis Tay, and Rosy Southwell. "Psychological Measurement in the Information Age: Machine-Learned Computational Models." Current Directions in Psychological Science 31, no. 1 (2022): 76–87. http://dx.doi.org/10.1177/09637214211056906.

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Psychological science can benefit from and contribute to emerging approaches from the computing and information sciences driven by the availability of real-world data and advances in sensing and computing. We focus on one such approach, machine-learned computational models (MLCMs)—computer programs learned from data, typically with human supervision. We introduce MLCMs and discuss how they contrast with traditional computational models and assessment in the psychological sciences. Examples of MLCMs from cognitive and affective science, neuroscience, education, organizational psychology, and pe

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Schwark, Jeremy D., Igor Dolgov, Daniel Hor, and William Graves. "Gender and Personality Trait Measures Impact Degree of Affect Change in a Hedonic Computing Paradigm." International Journal of Human-Computer Interaction 29, no. 5 (2013): 327–37. http://dx.doi.org/10.1080/10447318.2012.711703.

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Goyal, Ms Pooja, and Dr Sukhvinder Singh Deora. "Reliability of Trust Management Systems in Cloud Computing." Indian Journal of Cryptography and Network Security 1, no. 3 (2022): 1–5. http://dx.doi.org/10.54105/ijcns.c1417.051322.

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Cloud computing is an innovation that conveys administrations like programming, stage, and framework over the web. This computing structure is wide spread and dynamic, which chips away at the compensation per-utilize model and supports virtualization. Distributed computing is expanding quickly among purchasers and has many organizations that offer types of assistance through the web. It gives an adaptable and on-request administration yet at the same time has different security dangers. Its dynamic nature makes it tweaked according to client and supplier’s necessities, subsequently making it a

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Pooja, Goyal, and Singh Deora Sukhvinder. "Reliability of Trust Management Systems in Cloud Computing." Indian Journal of Cryptography and Network Security (IJCNS) 1, no. 3 (2022): 1–5. https://doi.org/10.54105/ijcns.C1417.051322.

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Cloud computing is an innovation that conveys administrations like programming, stage, and framework over the web. This computing structure is wide spread and dynamic, which chips away at the compensation per-utilize model and supports virtualization. Distributed computing is expanding quickly among purchasers and has many organizations that offer types of assistance through the web. It gives an adaptable and on-request administration yet at the same time has different security dangers. Its dynamic nature makes it tweaked according to client and supplier's necessities, subsequently making

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Cernian, Alexandra, Nicoleta Vasile, and Ioan Stefan Sacala. "Fostering Cyber-Physical Social Systems through an Ontological Approach to Personality Classification Based on Social Media Posts." Sensors 21, no. 19 (2021): 6611. http://dx.doi.org/10.3390/s21196611.

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The exponential increase in social networks has led to emergent convergence of cyber-physical systems (CPS) and social computing, accelerating the creation of smart communities and smart organizations and enabling the concept of cyber-physical social systems. Social media platforms have made a significant contribution to what we call human behavior modeling. This paper presents a novel approach to developing a users’ segmentation tool for the Romanian language, based on the four DISC personality types, based on social media statement analysis. We propose and design the ontological modeling app

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Shum, Kit-May, Michal Ptaszynski, and Fumito Masui. "Big Five Personality Trait Prediction Based on User Comments." Information 16, no. 5 (2025): 418. https://doi.org/10.3390/info16050418.

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The study of personalities is a major component of human psychology, and with an understanding of personality traits, practical applications can be used in various domains, such as mental health care, predicting job performance, and optimising marketing strategies. This study explores the prediction of Big Five personality trait scores from online comments using transformer-based language models, focusing on improving the model performance with a larger dataset and investigating the role of intercorrelations among traits. Using the PANDORA dataset from Reddit, the RoBERTa and BERT models, incl

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Kemp, Kathryn C., Jessica A. Kaczorowski, Christopher J. Burgin, et al. "Association of Multidimensional Schizotypy with PID-5 Domains and Facets." Journal of Personality Disorders 36, no. 6 (2022): 680–700. http://dx.doi.org/10.1521/pedi.2022.36.6.680.

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The underlying vulnerability for schizophrenia-spectrum disorders is expressed across a continuum of clinical and subclinical symptoms referred to as schizotypy. Schizotypy is a multidimensional construct with positive, negative, and disorganized dimensions. The present study examined associations of positive, negative, and disorganized schizotypy with pathological personality traits and facets assessed by the Personality Inventory for DSM-5 (PID-5) in 1,342 young adults. As hypothesized, positive schizotypy was associated with the PID-5 psychoticism domain and facets, negative schizotypy was

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Strang, Kenneth David. "Cybercrime Risk Found in Employee Behavior Big Data Using Semi-Supervised Machine Learning with Personality Theories." Big Data and Cognitive Computing 8, no. 4 (2024): 37. http://dx.doi.org/10.3390/bdcc8040037.

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A critical worldwide problem is that ransomware cyberattacks can be costly to organizations. Moreover, accidental employee cybercrime risk can be challenging to prevent, even by leveraging advanced computer science techniques. This exploratory project used a novel cognitive computing design with detailed explanations of the action-research case-study methodology and customized machine learning (ML) techniques, supplemented by a workflow diagram. The ML techniques included language preprocessing, normalization, tokenization, keyword association analytics, learning tree analysis, credibility/rel

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Lazarević, Ljiljana B., Michael Bošnjak, Goran Knežević, et al. "Disintegration as an Additional Trait in the Psychobiological Model of Personality." Zeitschrift für Psychologie 224, no. 3 (2016): 204–15. http://dx.doi.org/10.1027/2151-2604/a000254.

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Abstract. This meta-analytic study investigates the relations between Disintegration-like phenomena (i.e., various aspects of symptomatology with the prefix “schizo-,” both at the clinical and the subclinical level) and the traits of the Psychobiological Model of Personality (PBMP). The empirically based benchmark for assuming the distinctness of the trait Disintegration was .30. The sample included 26 manuscripts with 30 studies and 424 effect sizes. By computing inverse sampling variance weighted mean correlation coefficients under a random-effects assumption, the following associations were

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