The effect of personality on collaborative task performance and interaction

Collocated, multi-user technologies, which support group-work are becoming increasingly popular. Examples include MERL's Diamondtouch and Microsoft's Surface, both of which have evolved from research prototypes to commercial products. Many applications have been developed for such technologies which support the work and entertainment needs of small groups of people. None of these applications however, have been studied in terms of the interactions and performances of their users with regards to their personality. In this paper, we address this research gap by conducting a series of user studies involving dyads working on a number of multi-user applications on the DiamondTouch tabletop device

Tag clouds algorithm with the inclusion of personality traits

Tag clouds have emerged as the latest technique in information visualization using text analysis methods in a variety of situations to interpret unstructured data types. Literature review emphasizes that information visualization development techniques should include the personality traits of humans to provide effective and meaningful information. However, in the field of tag clouds, no published studies have investigated the role of personality traits to guide the design of tag cloud visualization. Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. Therefore, the main objective of this study is to develop an algorithm that can adapt visual features of tag cloud layout styles based on personality traits of the user. This study focuses on two visual features associated with personality traits, which are colors and shapes. To achieve the aim of this study, Design Science methodology was used through three main phases: problem identification, design of solution, and evaluation. The algorithm was developed based on three theories of personality traits, namely Myers-Briggs Type Indicator (MBTI), Shape, and Multiple Intelligence (MI). The algorithm was then tested through a black box testing. In addition, a prototype was developed to evaluate the proposed algorithm. Then, user satisfaction was conducted in order to evaluate this prototype using Q-SAFI instruments. Notable findings suggest that users are highly satisfied with colors and shapes of tag cloud as well as the overall tag cloud layout styles. The main contribution of this research is the tag cloud layout styles algorithm, which combines the concept of personality traits and characteristics of colors and shapes. This algorithm is beneficial for decision making using information visualization in which personality traits of the user are heavily inclined. Moreover, the tag cloud user’s satisfaction instrument, Q-SAFI, provides measurements for evaluating tag cloud visualization

The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison

Culturally influenced preferences in website aesthetics is a topic often neglected by scholars in human-computer interaction. Kim, Lee, and Choi (2003) identified aesthetic design factors of web home pages that elicited particular responses in South Korean web users based on 13 secondary emotional dimensions. This study extends Kim et al.'s work to U.S. participants, comparing the original South Korean findings with U.S. findings. Results show that U.S. participants reliably applied translations of the emotional adjectives used in the South Korean study to the home pages. However, factor analysis revealed that the aesthetic perceptions of U.S. and South Korean participants formed different aesthetic dimensions composed of different sets of emotional adjectives, suggesting that U.S. and South Korean people perceive the aesthetics of home pages differently. These results indicate that website aesthetics can vary significantly between cultures

Attributes of narrative game aesthetics for perceived cultural learning

Previous researches are mostly concerned on non-holistic game aesthetics for learning in various interactive media platforms. There is lack of studies on attributes of narrative games aesthetics which may contribute to perceived cultural learning. Therefore, this study aims to propose a conceptual model of narrative game aesthetics for perceived cultural learning. Three specific objectives were formulated: (i) to determine game aesthetics that contribute to perceived cultural learning in narrative games, (ii) to develop a narrative game based on the determined game aesthetics, and (iii) to produce empirical evidence on the contribution of game aesthetics towards perceived cultural learning. The research methodology comprises of three main phases: conceptual model development, prototype development, and user evaluation. For the first phase, the conceptual model was developed based on previous literature and reviewed by six experts. In the second phase, prototype development was then developed according to the conceptual model. Finally, user evaluation was employed using quasi experiment which involved 43 participants. Data analysis is conducted using descriptive analysis, correlation analysis, and observation. Findings indicate that six out of 10 attributes namely image and graphic; layout; shape and form; texture; voice; and music, are significantly correlated to perceived cultural learning. The observation results also indicate that these attributes can amplify game experience for perceived cultural learning. In a nutshell, this study has identified attributes of narrative game aesthetics for perceived cultural learning. It further provides empirical evidence on contributions of these attributes of narrative game aesthetics to perceived cultural learning. The outcome of this study will provide guidelines for narrative game designers and developers whom interested to inculcate cultural learning in their game

Chatbots’ extroverted or introverted personality’s influence on consumers’ purchase intention depending on consumers’ extroversion extent

The purpose of this study is to investigate the influence of chatbot personality on consumer purchase intention, depending on the consumer's level of extroversion. Through an experiment, this study will analyze the effects of extroverted and introverted chatbot personalities on consumers with different levels of extroversion. The findings will provide valuable insights into the impact of chatbot personality on consumers’ purchase intention and the potential for personalized communication strategies in e-commerce. Results indicate that chatbot perception significantly influences purchase intention and that a match in personality between the chatbot and the consumer leads to higher purchase intention. Additionally, extroverted chatbots are found to lead to higher purchase intention than introverted ones. Finally, perceived ease of chatbot use is shown to increase purchase intention. These findings suggest that providing chatbots with a personality can effectively enhance purchase intention, particularly if matching the consumer’s personalityO objectivo deste estudo é investigar a influência da personalidade do chatbot na intenção de compra do consumidor, dependendo do nível de extroversão do consumidor. Através de uma série de experiências, este estudo irá analisar os efeitos de personalidades extrovertidas e introvertidas de chatbots sobre consumidores com diferentes níveis de extroversão. Os resultados proporcionarão valiosos conhecimentos sobre o impacto da personalidade de chatbot na intenção de compra dos consumidores e o potencial para estratégias de comunicação personalizadas no comércio electrónico. Os resultados indicam que a percepção do chatbot influencia significativamente a intenção de compra e que uma correspondência na personalidade entre o chatbot e o consumidor leva a uma maior intenção de compra. Além disso, verifica-se que os chatbots extrovertidos levam a uma intenção de compra mais elevada do que os introvertidos. Finalmente, a percepção de facilidade de utilização do chatbot é aumenta a intenção de compra. Estas conclusões sugerem que dar uma personalidade aos chatbots pode efectivamente aumentar a intenção de compra

Tag cloud algorithm with the inclusion of personality traits

It is imperative to consider human different perspective in order to visualize the information data towards users.Many studies proved that personality traits are one of the most significant factors that must be considered to give meaningful value when us ers see a view.This study tries to give ample evidence toward adjusting visual features on tag cloud visualization techniques. Since there is no study has tried to create an algorithm that can customize tag cloud visual properties based on personality traits. Therefore, the main objective of this study is to make tag cloud algorithm with the inclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In addition, the utilization of RBS (rule bas e system) approach as artificial intelligent method is also taken into account to make knowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape .The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences

A comparison of what is part of usability testing in three countries

The cultural diversity of users of technology challenges our methods for usability evaluation. In this paper we report and compare three ethnographic interview studies of what is a part of a standard (typical) usability test in a company in Mumbai, Beijing and Copenhagen. At each of these three locations, we use structural and contrast questions do a taxonomic and paradigm analysis of a how a company performs a usability test. We find similar parts across the three locations. We also find different results for each location. In Mumbai, most parts of the usability test are not related to the interactive application that is tested, but to differences in user characteristics, test preparation, method, and location. In Copenhagen, considerations about the client´s needs are part of a usability test. In Beijing, the only varying factor is the communication pattern and relation to the user. These results are then contrasted in a cross cultural matrix to identify cultural themes that can help interpret results from existing laboratory research in usability test methods

Predicting Personality Traits Using Smartphone Sensor Data and App Usage Data

Human behavior is complex -- often defying explanation using traditional mathematical models. To simplify modeling, researchers often create intermediate psychological models to capture aspects of human behavior. These intermediate forms, such as those gleaned from personality inventories, are typically validated using standard survey instruments, and often correlate with behavior. Typically these constructs are used to predict stylized aspects of behavior. Novel sensing systems have made tracking behavior possible with unprecedented fidelity, posing the question as to whether the inverse process is possible: that is, inferring psychological constructs for individuals from behavioral data. Modern smartphones contain an array of sensors which can be filtered, combined, and analyzed to provide abstract measures of human behavior. Being able to extract a personal profile or personality type from data directly obtainable from a mobile phone without participant interaction could have applications for marketing or for initiating social or health interventions. In this work, we attempt to model a particularly salient and well-established personality inventory, the Big Five framework. Daily routines of participants were measured from parameters readily available from smartphones and supervised machine learning was used to create a model from that data. Cross validation-based evaluation demonstrated that the root mean squared error was sufficiently small to make actionable predictions about a person's personality from smartphone logs, but the model performed poorly for personality outliers

Perceived Visual Aesthetics of Emotionally Evocative Homepages: An Investigation of Affective Qualities Identified With Emotional Dimensions

Identified design factors for homepages that elicited aesthetic dimensions in Web users viewing homepages. However, their study was not crosscultural. The focus of this investigator’s study was to test 13 homepages used by Kim et al. with participants from the United States and determine whether the same aesthetic dimensions were evoked in U.S. participants. The resulting survey data of U.S. participants were compared with the survey data for South Korean participants. An initial analysis determined that U.S. participants generally agreed with South Korean participants about which aesthetic adjectives were in an aesthetic category. Other analyses showed no shared perceptions for homepages or adjective sets in aesthetic dimensions. This investigation suggested that aesthetic design principles for homepages from one culture are unlikely to predictably influence other cultures. A regression analysis was also used to investigate aesthetic design elements that prompt responses in U.S. participants