Browsing by Subject "Personality traits"
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Item Open Access Analyzing occupants' control over lighting systems in office settings using immersive virtual environments(Elsevier BV, 2021-06) Mahmoudzadeh, Parisa; Afacan, Yasemin; Adi, Muhamad NadimResearch has identified occupant behavior as one of the key contributors to building energy performance gap. Thus, this study systematically analyzed the impact of having personal control over lighting system on occupants' lighting choices, lighting satisfaction, and task performance in a virtual office setting. For this purpose, 30 participants took part in a 3-phased experiment with immersive virtual environments (IVEs). Each phase of the experiment offered a different degree of control over the lighting. Personality traits were also studied in relation to lighting choices. Finally, a technology acceptance model (TAM) was employed to further investigate the participants’ attitude towards the virtual reality (VR) technology. The findings of this study showed that using an interactive lighting system, which was as satisfactory compared to a conventional lighting system, encouraged the participants to use more natural light. The interactive lighting system imposed the same amount of cognitive load on the participants for performing a reading task as a conventional lighting system, which was significantly lower than their cognitive load scores for performing the task with automated lighting system. Personality analyses demonstrated that the participants with a high score on openness had a wide range of lighting choices either with conventional or with interactive lighting. This study's results differed from the previous studies by highlighting that the participants considered VR as a better fit to an enjoyable experience rather than a useful tool for performing serious tasks.Item Open Access Analyzing occupants’ control over lighting systems in office settings using virtual environments(Bilkent University, 2020-12) Mahmoudzadeh, ParisaThis study systematically analyzed the impact of having personal control over lighting system on occupants’ lighting choices, lighting satisfaction, and task performance in a virtual office setting. For this purpose, 30 participants took part in a 3-phased experiment with immersive virtual environments (IVEs). Each phase of the experiment offered a different degree of control over the lighting. Personality traits were also studied in relation to lighting choices. Finally, a technology acceptance model (TAM) was employed to further investigate the participants’ attitude towards the virtual reality (VR) technology. The findings of this study showed that using an interactive lighting system, which was as satisfactory compared to a conventional lighting system, encouraged the participants to use more natural light. The interactive lighting system imposed the same amount of cognitive load on the participants for performing a reading task as a conventional lighting system, which was significantly lower than their cognitive load scores for performing the task with automated lighting system. Personality analyses demonstrated that the participants with a high score on openness had a wide range of lighting choices either with conventional or with interactive lighting. This study’s results differed from the previous studies by highlighting that the participants considered VR as a better fit to an enjoyable experience rather than as a useful tool for performing serious tasks.Item Open Access Creating crowd variation with the OCEAN personality model(IFAAMAS, 2008-05) Durupınar, Funda; Allbeck, J.; Pelechano, N.; Badler, N.Most current crowd simulators animate homogeneous crowds, but include underlying parameters that can be tuned to create variations within the crowd. These parameters, however, are specific to the crowd models and may be difficult for an animator or naive user to use. We propose mapping these parameters to personality traits. In this paper, we extend the HiDAC (High-Density Autonomous Crowds) system by providing each agent with a personality model in order to examine how the emergent behavior of the crowd is affected. We use the OCEAN personality model as a basis for agent psychology. To each personality trait we associate nominal behaviors; thus, specifying personality for an agent leads to an automation of the low-level parameter tuning process. We describe a plausible mapping from personality traits to existing behavior types and analyze the overall emergent crowd behaviors. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.Item Open Access Cross cultural differences in materialism(Elsevier, 1996) Ger, G.; Belk, R. W.Materialism was explored in twelve countries using qualitative data, measures of consumer desires, measures of perceived necessities, and adapted versions of the Belk (1985) materialism scales with student samples. The use of student samples and provisionary evidence for cross-cultural reliability and validity for the scales, make the quantitative results tentative, but they produced some interesting patterns that were also supported by the qualitative data. Romanians were found to be the most materialistic, followed by the U.S.A., New Zealand, Ukraine, Germany, and Turkey. These results suggest that materialism is neither unique to the West nor directly related to affluence, contrary to what has been assumed in prior treatments of the development of consumer culture.Item Open Access Multimodal video-based personality recognition using Long Short-Term Memory and convolutional neural networks(Bilkent University, 2019-07) Aslan, SüleymanPersonality computing and affective computing, where recognition of personality traits is essential, have gained increasing interest and attention in many research areas recently. The personality traits are described by the Five-Factor Model along five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. We propose a novel approach to recognize these five personality traits of people from videos. Personality and emotion affect the speaking style, facial expressions, body movements, and linguistic factors in social contexts, and they are affected by environmental elements. For this reason, we develop a multimodal system to recognize apparent personality traits based on various modalities such as the face, environment, audio, and transcription features. In our method, we use modality-specific neural networks that learn to recognize the traits independently and we obtain a final prediction of apparent personality with a feature-level fusion of these networks. We employ pre-trained deep convolutional neural networks such as ResNet and VGGish networks to extract high-level features and Long Short-Term Memory networks to integrate temporal information. We train the large model consisting of modality-specific subnetworks using a two-stage training process. We first train the subnetworks separately and then fine-tune the overall model using these trained networks. We evaluate the proposed method using ChaLearn First Impressions V2 challenge dataset. Our approach obtains the best overall “mean accuracy” score, averaged over five personality traits, compared to the state-of-the-art.Item Open Access Perceptions of transformational leadership and job satisfaction: The roles of personality traits and psychological empowerment(Cambridge University Press, 2018) Aydogmus, C.; Camgoz, S. M.; Ergeneli, A.; Ekmekci, O. T.Through two studies, this paper investigates the moderating effects of personality traits (i.e., extraversion, conscientiousness, agreeableness and neuroticism) and the mediating effect of psychological empowerment on the relationship between perceived transformational leadership and job satisfaction. Study 1 searches whether personality traits moderate the effects of perceived transformational leadership on followers' job satisfaction. Using a sample of 221 R&D employees employed by information technology organizations, the results of Study 1 indicate that the more conscientious the employee, the stronger the relationship between perceived transformational leadership and job satisfaction. Study 2 explores whether psychological empowerment mediates the effects of perceived transformational leadership on followers' job satisfaction. Based on data from 348 academics, the results support the mediating role of psychological empowerment on job satisfaction, in that when employees perceive their leader as transformational they feel more psychologically empowered, which in turn increases job satisfaction levels. Implications for future research and practice are discussed.Item Open Access Predicting personality traits with semantic structures and LSTM-based neural networks(Elsevier, 2022-10) Kosan, Muhammed Ali; Karacan, Hacer; Ürgen, Burcu AyşenThere is a need to obtain more information about target audiences in many areas such as law enforcement agencies, institutions, human resources, and advertising agencies. In this context, in addition to the information provided by individuals, their personal characteristics are also important. In particular, the predictability of personality traits of individuals is seen as a major parameter in making decisions about individuals. Textual and media data in social media, where people produce the most data, can provide clues about people's personal lives, characteristics, and personalities. Each social media environment may contain different assets and structures. Therefore, it is important to make a structural analysis according to the social media platform. There is also a need for a labelled dataset to develop a model that can predict personality traits from social media data. In this study, first, a personality dataset was created which was retrieved from Twitter and labelled with IBM Personality Insight. Then the unstructured data were transformed into meaningful and processable data, LSTM-based prediction models were created with the structural analysis, and evaluations were made on both our dataset and PAN-2015-EN. © 2022 THE AUTHORSItem Open Access Teaching style and personality traits as predictors of socio-affective learning strategies: findings from translation studies students of a private Turkish university(Bilkent University, 2022-02) Gürbüz, Ezgi SenaThe present study aimed to investigate to what extent the personality traits and perceived teacher autonomy support of university students related to their preferred affective and social language learning strategies. The study was carried out at an English-speaking private university in Ankara. The participants of the study were 102 students (65% female, 33% male, 2% other) studying Translation and Interpretation in English and French. Bivariate correlation analysis revealed that among students’ personality traits only agreeableness was positively related to students’ affective and social learning strategies. Furthermore, perceived-autonomy support was correlated to both affective and social learning strategies. According to hierarchical regression analysis, only perceived-autonomy support predicted affective learning strategies when both personality traits and perceived-autonomy support were considered as predictors. However, agreeableness personality trait and perceived-autonomy support both positively predicted students’ social learning strategies. The importance of students’ autonomy support for enhancing affective and social learning strategies is highlighted in the implications of the study for curriculum and instruction.