The Effectiveness of Personalized Movie Explanations : An Experiment Using Commercial Meta-data

Preprin

Exploring personality-targeted UI design in online social participation systems

We present a theoretical foundation and empirical findings demonstrating the effectiveness of personality-targeted design. Much like a medical treatment applied to a person based on his specific genetic profile, we argue that theory-driven, personality-targeted UI design can be more effective than design applied to the entire population. The empirical exploration focused on two settings, two populations and two personality traits: Study 1 shows that users' extroversion level moderates the relationship between the UI cue of audience size and users' contribution. Study 2 demonstrates that the effectiveness of social anchors in encouraging online contributions depends on users' level of emotional stability. Taken together, the findings demonstrate the potential and robustness of the interactionist approach to UI design. The findings contribute to the HCI community, and in particular to designers of social systems, by providing guidelines to targeted design that can increase online participation. Copyright © 2013 ACM

Persuasive technologies in building support system to prevent non-communicable diseases caused by sedentary lifestyle

In this paper, we present the use of persuasion to help people who want to change their everyday behavior technologies. Méxmov and Lifestyle Change Recommender Systems (LSCS) ¡Camina!, are designed to reduce sedentary as prevention of non-communicable diseases.VI Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras de Informática (RedUNCI

Persuasive technologies in building support system to prevent non-communicable diseases caused by sedentary lifestyle

In this paper, we present the use of persuasion to help people who want to change their everyday behavior technologies. Méxmov and Lifestyle Change Recommender Systems (LSCS) ¡Camina!, are designed to reduce sedentary as prevention of non-communicable diseases.VI Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras de Informática (RedUNCI

The influence of national culture on the attitude towards mobile recommender systems

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study aimed to identify factors that influence user attitudes towards mobile recommender systems and to examine how these factors interact with cultural values to affect attitudes towards this technology. Based on the theory of reasoned action, belief factors for mobile recommender systems are identified in three dimensions: functional, contextual, and social. Hypotheses explaining different impacts of cultural values on the factors affecting attitudes were also proposed. The research model was tested based on data collected in China, South Korea, and the United Kingdom. Findings indicate that functional and social factors have significant impacts on user attitudes towards mobile recommender systems. The relationships between belief factors and attitudes are moderated by two cultural values: collectivism and uncertainty avoidance. The theoretical and practical implications of applying theory of reasoned action and innovation diffusion theory to explain the adoption of new technologies in societies with different cultures are also discussed.National Research Foundation of Korea Grant funded by the Korean governmen

IMPROVING THE DEPENDABILITY OF DESTINATION RECOMMENDATIONS USING INFORMATION ON SOCIAL ASPECTS

Prior knowledge of the social aspects of prospective destinations can be very influential in making travel destination decisions, especially in instances where social concerns do exist about specific destinations. In this paper, we describe the implementation of an ontology-enabled Hybrid Destination Recommender System (HDRS) that leverages an ontological description of five specific social attributes of major Nigerian cities, and hybrid architecture of content-based and case-based filtering techniques to generate personalised top-n destination recommendations. An empirical usability test was conducted on the system, which revealed that the dependability of recommendations from Destination Recommender Systems (DRS) could be improved if the semantic representation of social attributes information of destinations is made a factor in the destination recommendation process

Social learning approach in designing persuasive e-commerce recommender system model

Intention to purchase in existing online business practice is learned through observation of information display by online seller. The emergent growth of persuasive technologies currently holds a great potential in driving a positive influence towards consumer purchase behavior. But to date, there is still limited research on implementing persuasion concept into the recommender system context. Drawing upon the principle design of persuasive system, the main purpose of this study is to explore social learning advantages in creating persuasive features for E-Commerce recommender system. Based on Social Cognitive Theory, the influence of personal and environmental factors will be examined in measuring consumer purchase intention. In addition, dimensions of social learning environment are represented by observational learning theory and cognitive learning theory. From those reviews, this study assumed that social learning environment can be created based on attentiveness, retentiveness, motivational, knowledge awareness and interest evaluation cues of consumer learning factors. Furthermore, the persuasive environment of recommender system is assumed to have positive influence towards individual characteristics such as self-efficacy behavior, perceived task complexity and confused by over choice. Findings from those reviews have contributed to the development of a research model in visualizing social learning environment that can be used to develop a persuasive recommender system in E-Commerce and hence measures the impact towards consumer purchase intention

Evaluating the effectiveness of explanations for recommender systems : Methodological issues and empirical studies on the impact of personalization

Peer reviewedPostprin

Recommender systems and their ethical challenges

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system