Towards Psychometrics-based Friend Recommendations in Social Networking Services

Two of the defining elements of Social Networking Services are the social profile, containing information about the user, and the social graph, containing information about the connections between users. Social Networking Services are used to connect to known people as well as to discover new contacts. Current friend recommendation mechanisms typically utilize the social graph. In this paper, we argue that psychometrics, the field of measuring personality traits, can help make meaningful friend recommendations based on an extended social profile containing collected smartphone sensor data. This will support the development of highly distributed Social Networking Services without central knowledge of the social graph.Comment: Accepted for publication at the 2017 International Conference on AI & Mobile Services (IEEE AIMS

The Influence of Personality Traits on Mobile Phone Application Preferences

Understanding mobile phone users' preferences and behavior is essential for the commercial success of new application development. This study aims to enhance this understanding by identifying the personality traits associated with smart phone application use. Multiple regressions were used to analyze results from a sample of 233 participants. Consistent with recent personality research, we found that the "Big Five" personality dimensions are related to the application of smartphone technology. Extroverted individuals reported greater importance on gaming applications, but they viewed productivity applications as less important. Also, neurotics placed greater importance on travel applications, while less conscientious people indicated that communication, productivity, and utilities applications were less important to them

Smartphone OS and User Emotion and Ethics

In the light of Gosling theory, we want to answer the question of whether the moral and emotional characteristics (as their Identity Claims and Emotional Regulation) of different smartphones platforms users differ. For this purpose we conducted two researches on a sample of 1500 Serbian students. The obtained results point to the fact that there are statistically significant differences in morality of users of different OS (other socio demographic variables have no significant influence on our dependent variables). Moral characteristics were operationally defined with the Moral Foundations Theory by Haidt. In the second research 809 subjects completed the PANAS X questionnaire. Significant discrete emotions and mood differences were found among different smartphone OS users

Loyalty towards online games, gaming addiction, and purchase intention towards online mobile in-game features

The most important stream of game developers' revenue is arguably via gamer's in-game purchases. Previous literature has identified a number of strong determinants of online purchase intention including values, consumer experience, lifestyle, security, perceived risk, information, and subjective norms and behavioural control. The present study examined the relationship between online mobile gaming addiction and loyalty towards purchase intention of online mobile game in-game apps. The present study comprised 430 students from two major Indian universities who completed a short 28-item survey focusing on three variables (i.e., addiction, loyalty towards online games, and purchase intention towards online mobile in-game features). The results demonstrated that (i) online mobile game addiction shared a significant positive relationship with online mobile game loyalty; (ii) online mobile game addiction had a positive relationship with the purchase of online mobile in-game apps, and (iii) online mobile game loyalty increased game users' intention to purchase online mobile in-game apps. The present study is the first to investigate loyalty and gaming addiction in relation to the purchase of in-game apps. Game developers will always want to facilitate loyalty among its clientele. However, if the engagement strategies used by gaming operators facilitate addiction as a way of increasing purchase intention of online mobile game in-game apps, this raises serious ethical questions which the gaming industry need to address as part of its corporate social responsibility strategy

When phones get personal : Predicting Big Five personality traits from application usage

As smartphones are increasingly an integral part of daily life, recent literature suggests a deeper relationship between personality traits and smartphone usage. However, this relationship depends on many complex factors such as geographic location, demographics, or cultural influence, just to name a few. These factors provide crucial knowledge for e.g. usage support, recommendations, marketing, general usage improvements. We use six months of application usage data from 739 Android smartphone user together with the IPIP 50-item Big Five personality traits questionnaire. As our main contribution, we show that even category-level aggregated application usage can predict Big Five traits at up to 86%-96% prediction fit in our sample. Our results show the effect of personality traits on application usage (mean error improvement on random guess 17.0%). We also identify which application usage data best describe the Big Five personality traits. Our work enables future personality-driven research, and shows that when studying personality, application categories can provide sufficient predictions in general traits. (C) 2020 The Authors. Published by Elsevier B.V.Peer reviewe

Are you “phubbing” me? The Determinants of Phubbing Behavior and Assessment of Measurement Invariance across Sex Differences

Phubbing behavior is pervasive but the examination of the determinants and measurement invariance remain deficient. The present study aims to investigate: (1) relationships between Big Five personality traits (i.e., open-mindedness, conscientiousness, extraversion, agreeableness, and negative emotionality), coping styles (i.e., problem-focused and emotional-focused), Internet addiction and phubbing behavior; (2) the mediating role of Internet addiction among these relationships; and (3) measurement invariance across sex groups. A total of 405 responses were included in the final analyses. Participants were sampled using a probability-proportionate-to-size (PPS) method. Data were collected using paper-and-pencil survey: Phubbing Scale, Internet Addiction Test, Big Five Inventory, and Simplified Coping Styles Questionnaire. Negative emotionality, open-mindedness, and Internet addiction were the significant determinants of phubbing behavior. Internet addiction partially mediates open-mindedness and phubbing behavior. As for measurement invariance across sex groups, conscientiousness, extraversion, negative emotionality, Internet addiction, and phubbing behavior constructs achieved full measurement invariance. The agreeableness construct showed partial measurement invariance. Three constructs (i.e., open-mindedness, problem-focused and emotional-focused coping) failed to achieve partial measurement invariance, signifying that male and female participants had different interpretations on the items of these constructs. This pervasive culture could be gradually weakened if in-person interaction is intensely promoted

Personality Traits as Predictors of Online Customer Review Motivations

Online customer reviews (OCRs) are becoming increasingly popular among consumers who read them to make informed decisions about products and services. This study investigates consumers’ motivations for posting OCRs and the relationship between the motivations and the Big Five personality traits. The data come from an online sample of 352 online users who reported posting a review of a good or service. The results of the study indicate that individuals who post OCRs are driven primarily by interest in helping other consumers, followed by economic incentives, venting, self-efficacy, and social interaction. Using regression analyses, agreeableness was found to be positively related to interest in helping others and economic incentives, but negatively related to the venting motivation. Extraversion was found to be positively related to social interaction. Further exploration using canonical correlation analysis revealed a cluster of association between self-interested helpers (i.e., those motivated by economic incentives and the desire to help other consumers) and the Big Five personality traits of agreeableness and extraversion. Practical implications of these findings are discussed, as well as suggestions for future research

Investigation of university students’ problematic usage of mobile phone in the context of personalityÜniversite öğrencilerinde cep telefonunun problemli kullanımının kişilik bağlamında incelenmesi

Aim of this study is to examine problematic usage of mobile phone in the context of big five personality among university students. 103 male and 182 female, totally 285 university students who were from different Departments of Faculty of Education composed participants of the study in the spring period 2015-2016 academic year. Problematic mobile phone usage scale (PMPUS) and Quick Big Five Personality Test (QBFPT) were applied to 285 students, who were participants of the study. To analyse these data, Pearson’s Correlation Coefficient, Cronbach’s Alpha Coefficients, skewness, kurtosis, t test, and multiple regression were used. According to results obtained from the study, there was no significant difference between male and female in relation to problematic usage of mobile phone. Furthermore, agreeableness, extraversion, and openness to experience didn’t statistically predict to problematic usage of mobile phone, but conscientiousness and emotional stability statistically did. Discussion and some suggestions have been made based on the findings. ÖzetBu araştırmanın amacı üniversite öğrencilerinin cep telefonlarını problemli kullanma davranışlarını beş büyük kişilik bağlamında incelemektir. Araştırmanın katılımcılarını 2015-2016 Eğitim-Öğretim sezonunun bahar döneminde Eğitim Fakültesi’nde öğrenim görmekte olan 103’ü erkek, 182’si kadın olan toplamda 285 üniversite öğrencisi oluşturmaktadır. Araştırmanın katılımcılarına üniversite öğrencileri için problemli cep telefonu kullanım ölçeği (PCTKÖ) ve hızlı büyük beşli kişilik testi (HBBKT) uygulanmıştır. Elde edilen verilerin analizinde Pearson Korelasyon Katsayısı, iç tutarlılığa ilişkin güvenirlik katsayısını hesaplamak için Cronbach Alpha katsayıları, basıklık ve çarpıklık değerleri, cep telefonunun problemli kullanımının cinsiyete göre farklılaşıp farklılaşmadığını belirlemek için t testi ve son olarak da beş kişilik faktörünün cep telefonunun problemli kullanımını yordayıp yordamadığına ilişkin çoklu regresyon analizi yapılmıştır. Araştırmadan elde edilen sonuca göre, cep telefonunun problemli kullanımı cinsiyete göre istatistiksel olarak anlamlı bir farklılığın olmadığı bulunmuştur. Ayrıca uyumluluk, dışadönüklük ve deneyime açıklık kişilik faktörlerinin cep telefonunun problemli kullanımını istatistiksel olarak anlamlı bir şekilde yordamadığı; ancak duygusal denge ve sorumluluk kişilik faktörlerinin istatistiksel olarak anlamlı bir şekilde yordadığı belirlenmiştir. Elde edilen bulgulara dayalı olarak önerilerde bulunulmuş ve tartışılmıştır

Mining large-scale smartphone data for personality studies

In this paper, we investigate the relationship between automatically extracted behavioral characteristics derived from rich smartphone data and self-reported Big-Five personality traits (extraversion, agreeableness, conscientiousness, emotional stability and openness to experience). Our data stem from smartphones of 117 Nokia N95 smartphone users, collected over a continuous period of 17months in Switzerland. From the analysis, we show that several aggregated features obtained from smartphone usage data can be indicators of the Big-Five traits. Next, we describe a machine learning method to detect the personality trait of a user based on smartphone usage. Finally, we study the benefits of using gender-specific models for this task. Apart from a psychological viewpoint, this study facilitates further research on the automated classification and usage of personality traits for personalizing services on smartphone