User Perceptions of Mobile Banking Apps in Tanzania: Impact of Information Systems (IS) Factors and Customer Personality Traits

This study probes the roles that information systems (IS) success factors and user personality traits play in Tanzanian users’ perceptions of their experiences with mobile banking apps. Based on a survey of 249 mobile banking customers, the study finds that users are being positively influenced by the apps’ system quality and system service, but not by the apps’ information quality. The study also finds that, with respect to user personality traits, openness, agreeableness, conscientiousness and extraversion are all traits that have a positive impact on customers’ use of, and satisfaction with, mobile banking apps. The findings suggest that developers of mobile banking apps for the Tanzanian market need to both improve the quality of the information in the apps and continue to target a range of personality traits.

Predicting user personality with social interactions in Weibo

PurposeThe purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user interaction behavior on social media and (2) examine whether social interaction data on social media platforms can predict user personality.Design/methodology/approachSocial interaction data was collected from 198 users of Sina Weibo, a popular social media platform in China. Their personality traits were also measured via questionnaire. Machine learning techniques were applied to predict the personality traits based on the social interaction data.FindingsThe results demonstrated that the proposed classifiers had high prediction accuracy, indicating that our approach is reliable and can be used with social interaction data on social media platforms to predict user personality. “Reposting,” “being reposted,” “commenting” and “being commented on” were found to be the key interaction features that reflected Weibo users' personalities, whereas “liking” was not found to be a key feature.Originality/valueThe findings of this study are expected to enrich personality prediction research based on social media data and to provide insights into the potential of employing social media data for the purpose of personality prediction in the context of the Weibo social media platform in China.

A psychologically-inspired fuzzy-based approach for user personality prediction in rumor propagation across social networks

Social networks have emerged as a fertile ground for the spread of rumors and misinformation in recent times. The increased rate of social networking owes to the popularity of social networks among the common people and user personality has been considered as a principal component in predicting individuals’ social media usage patterns. Several studies have been conducted to study the psychological factors influencing the social network usage of people but only a few works have explored the relationship between the user’s personality and their orientation to spread rumors. This research aims to investigate the effect of personality on rumor spread on social networks. In this work, we propose a psychologically-inspired fuzzy-based approach grounded on the Five-Factor Model of behavioral theory to analyze the behavior of people who are highly involved in rumor diffusion and categorize users into the susceptible and resistant group, based on their inclination towards rumor sharing. We conducted our experiments in almost 825 individuals who shared rumor tweets on Twitter related to five different events. Our study ratifies the truth that the personality traits of individuals play a significant role in rumor dissemination and the experimental results prove that users exhibiting a high degree of agreeableness trait are more engaged in rumor sharing activities and the users high in extraversion and openness trait restrain themselves from rumor propagation.