User interface personalization in news apps

News is increasingly being accessed on smartphones and tablets, establishing mobile news reading as one of the most popular activities on mobile devices. News reading is also a very individual activity with marked differences in the way people read and access the news, however, news apps have limited personalization. In this paper, we approach news personalization as a two-dimensional problem. We discuss news personalization in terms of 'what' content is delivered to the user and 'how' that content is consumed. We present our approach towards user interface personalization in news apps and we conclude that news content recommendation and user interface personalization should co-exist in news apps

User Interface Personalization in News Apps

ABSTRACT News is increasingly being accessed on smartphones and tablets, establishing mobile news reading as one of the most popular activities on mobile devices. News reading is also a very individual activity with marked differences in the way people read and access the news, however, news apps have limited personalization. In this paper, we approach news personalization as a two-dimensional problem. We discuss news personalization in terms of 'what' content is delivered to the user and 'how' that content is consumed. We present our approach towards user interface personalization in news apps and we conclude that news content recommendation and user interface personalization should co-exist in news apps

Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions

Technology has recently been recruited in the war against the ongoing obesity crisis; however, the adoption of Health & Fitness applications for regular exercise is a struggle. In this study, we present a unique demographically representative dataset of 15k US residents that combines technology use logs with surveys on moral views, human values, and emotional contagion. Combining these data, we provide a holistic view of individuals to model their physical exercise behavior. First, we show which values determine the adoption of Health & Fitness mobile applications, finding that users who prioritize the value of purity and de-emphasize values of conformity, hedonism, and security are more likely to use such apps. Further, we achieve a weighted AUROC of .673 in predicting whether individual exercises, and we also show that the application usage data allows for substantially better classification performance (.608) compared to using basic demographics (.513) or internet browsing data (.546). We also find a strong link of exercise to respondent socioeconomic status, as well as the value of happiness. Using these insights, we propose actionable design guidelines for persuasive technologies targeting health behavior modification

Business plan for the mobile application "DNow"

The purpose of this business plan is to analyse the viability of the mobile app DNow, mobile application with personalized news. Even though DNow might be a great product, that is not enough for it to be successful without a strong plan. We started by conducting a market analysis to have a better understanding of the mobile market in Spain and the consumers of information in Navarre. The results from the researches showed an increasing popularity of the smartphones in Spain, and a clear change in the behaviour of the consumers of information. The interviews showed that the people like to be informed about what interests them and they perceive that the newspapers publish too much information and it is impossible to consume all of it. The results from the survey showed that the smartphones and apps are very popular and the respondents liked the idea of an app with personalized news. Since the results from the market analysis seemed to confirm a want for personalized news, we decided to continue the plan, and design a marketing plan for DNowGraduado o Graduada en Administración y Dirección de Empresas por la Universidad Pública de NavarraEnpresen Administrazio eta Zuzendaritzan Graduatua Nafarroako Unibertsitate Publikoa

Towards Design Excellence for Context-Aware Services - The Case of Mobile Navigation Apps

To satisfy service customers and create unique value in a digitized world, companies must strive for exceeding customers’ expectations of e-service experience by establishing high e-service quality. However, an increasing amount of e-services is performed by context-aware mobile technology, which is able to sense and react to changes in the user’s environment. Although these context-aware services are able to address our personal needs and already determine our everyday live, knowledge on how to develop such services is sparse. In our study, we qualitatively compare three mobile navigation apps based on their user reviews in order to elicit first requirements and design approaches for e-service quality oriented design. Results show that well known e-service quality models are not fully applicable to the case of mobile navigation services

Towards an institutional PLE

PLEs in their broader sense (the ad-hoc, serendipitous and potentially chaotic set of tools that learners bring to their learning) are increasingly important for learners in the context of formal study. In this paper we outline the approach that we are taking at the University of Southampton in redesigning our teaching and learning infrastructure into an Institutional PLE. We do not see this term as an oxymoron. We define an Institutional PLE as an environment that provides a personalised interface to University data and services and at the same time exposes that data and services to a student’s personal tools. Our goal is to provide a digital platform that can cope with an evolving learning and teaching environment, as well as support the social and community aspects of the institution

Recommendation System for News Reader

Recommendation Systems help users to find information and make decisions where they lack the required knowledge to judge a particular product. Also, the information dataset available can be huge and recommendation systems help in filtering this data according to users‟ needs. Recommendation systems can be used in various different ways to facilitate its users with effective information sorting. For a person who loves reading, this paper presents the research and implementation of a Recommendation System for a NewsReader Application using Android Platform. The NewsReader Application proactively recommends news articles as per the reading habits of the user, recorded over a period of time and also recommends the currently trending articles. Recommendation systems and their implementations using various algorithms is the primary area of study for this project. This research paper compares and details popular recommendation algorithms viz. Content based recommendation systems, Collaborative recommendation systems etc. Moreover, it also presents a more efficient Hybrid approach that absorbs the best aspects from both the algorithms mentioned above, while trying to eliminate all the potential drawbacks observed

My friends, editors, algorithms, and I: Examining audience attitudes to news selection

Prompted by the ongoing development of content personalization by social networks and mainstream news brands, and recent debates about balancing algorithmic and editorial selection, this study explores what audiences think about news selection mechanisms and why. Analysing data from a 26-country survey (N=53,314), we report the extent to which audiences believe story selection by editors and story selection by algorithms are good ways to get news online and, using multi-level models, explore the relationships that exist between individuals’ characteristics and those beliefs. The results show that, collectively, audiences believe algorithmic selection guided by a user’s past consumption behaviour is a better way to get news than editorial curation. There are, however, significant variations in these beliefs at the individual level. Age, trust in news, concerns about privacy, mobile news access, paying for news, and six other variables had effects. Our results are partly in line with current general theory on algorithmic appreciation, but diverge in our findings on the relative appreciation of algorithms and experts, and in how the appreciation of algorithms can differ according to the data that drive them. We believe this divergence is partly due to our study’s focus on news, showing algorithmic appreciation has context-specific characteristics