Understanding and mitigating the impact of Internet demand in everyday life

Digital devices and online services are increasingly embedded within our everyday lives. The growth in usage of these technologies has implications for environmental sustainability due to the energy demand from the underlying Internet infrastructure (e.g. communication networks, data centres). Energy efficiencies in the infrastructure are important, but they are made inconsequential by the sheer growth in the demand for data. We need to transition users’ Internet-connected practices and adapt HumanComputer Interaction (HCI) design in less demanding and more sustainable directions. Yet it’s not clear what the most data demanding devices and online activities are in users’ lives, and how this demand can be intervened with most effectively through HCI design. In this thesis, the issue of Internet demand is explored—uncovering how it is embedded into digital devices, online services and users’ everyday practices. Specifically, I conduct a series of experiments to understand Internet demand on mobile devices and in the home, involving: a large-scale quantitative analysis of 398 mobile devices; and a mixed-methods study involving month-long home router logging and interviews with 20 participants (nine households). Through these studies, I provide an in-depth understanding of how digital activities in users’ lives augment Internet demand (particularly through the practice of watching), and outline the roles for the HCI community and broader stakeholders (policy makers, businesses) in curtailing this demand. I then juxtapose these formative studies with design workshops involving 13 participants; these discover how we can reduce Internet demand in ways that users may accept or even want. From this, I provide specific design recommendations for the HCI community aiming to alleviate the issue of Internet growth for concerns of sustainability, as well as holistically mitigate the negative impacts that digital devices and online services can create in users’ lives

Using Mass Media And Social Media For The Prevention Of Non-Communicable Diseases

Non-communicable diseases (NCDs) such as diabetes, cancers, and cardiovascular disease, share modifiable risk factors, with overweight and obesity, physical inactivity, and poor nutrition being among the most important of these. One public health strategy that has been widely employed to address these risk factors and reduce the burden of NCDs is mass media campaigns (MMCs). These campaigns use multiple channels – including television, radio, billboards, online, and increasingly social media – to communicate messages about the promotion of health and the prevention of the disease. The aim is to reach as many people in the target population as possible, with the expectation that doing so will maximise the campaign’s impact on the population's health. However, gaps in the scientific literature are such that knowledge about what works in NCD-related MMCs is limited. First, those campaigns that have been evaluated have consistently shown positive impacts on awareness, knowledge, and other intermediate outcomes, but it is rare for a campaign to demonstrate behaviour change. Second, the existing evidence is ageing quickly due to the rapid change in media consumption habits over the last decade, including the rapid uptake of Facebook and other social media. Finally, while there are theories, such as the Hierarchy of Effects model, that purport to explain how campaigns influence behaviour change, these have rarely been tested, meaning that their accuracy and usefulness is unknown. Collectively, these gaps make it difficult to identify effective components of MMCs, which is problematic given that governments use these types of campaigns often and that they are usually expensive to design and implement. In this thesis, I present research that addresses these gaps. My research provides insight into the impact of MMCs on health-related outcomes and furthers our understanding of best practice in the planning, implementation, and evaluation of mass media and social media campaigns. Specifically, my research aims to identify and critique current practice within overweight and obesity prevention campaigns, identify the strengths and limitations of current practices on Facebook as a component of campaigns, and determine the impact of the recent New South Wales (NSW) Government’s Make Healthy Normal (MHN) overweight and obesity prevention campaign. To address these aims, I conducted seven studies, using both quantitative and qualitative methods. These studies provide new and valuable insights into improving campaigns and creating engaging content on Facebook. Collectively, the findings indicate that, while campaigns can be effective in increasing knowledge about a health issue, increasing knowledge is insufficient and may not even be necessary to have a meaningful impact on health. This raises questions around the role of MMCs in responding to health issues like obesity. The research also suggests that while there is real potential to use Facebook as an effective component of campaigns, more consideration should be given to exactly what role Facebook (or other social media) should play within a broader campaign. Finally, it is important that the theories that underpin campaigns be tested and refined. Doing so will mean that effective features of communications campaigns can be identified and increase the likelihood that future campaigns will contribute to solving complex prevention problems

A Retrospective Analysis of Maternal and Child Outcomes Following an Obesity Intervention Program

Background: One of the highest risk groups for childhood obesity and associated co-morbidities in the United States are low-income Hispanic preschool children. To reduce obesity, effective interventions are being sought to improve health behaviors among high risks groups. Objectives: To evaluate a subset of data from a larger 9-month promotora facilitated obesity intervention study. The aims were to determine: 1) pre- to post-program differences in health behaviors including: (a) children\u27s consumption of high carbohydrate beverages (HCB); and (b) maternal walking, beliefs, knowledge, self-efficacy, and relationship building regarding nutrition and physical activity; and 2) which covariates were significant for change in outcome variables. Methods: A retrospective data analysis, pre post single group design was used to analyze a subset of data from the larger study consisting of a case sample of 33 low-income, Hispanic mothers (18- to 35-year-olds) with pre-school children (3- to 5-year-olds). Differences in outcome variables for related samples between baseline and 9 months were examined using: descriptive statistics, a matched-pairs t-test, the Wilcoxon signed-ranks test, and the chi-square test. Pearson and Spearman correlations were performed to assess relationships between covariates and outcome variables, and if regression analysis assumptions were met. A backward step-wise linear regression was run to determine covariates significant for change in health behaviors. Results: From baseline to 9 months, there was a 56% decrease in children\u27s overall HCB consumption (soda, 100% juice, and sugary drinks); a 47% increase in water consumption; and a 58% increase in total maternal steps (Tuesday and Saturday). By 9 months, maternal beliefs were more positive about walking, knowledge increased about healthy drinks, and maternal self-efficacy improved regarding role modeling healthy behaviors. Gravida was correlated with increased Saturday steps and increased water consumption; and promotora visits were correlated with increased consumption of soda. Implications: Findings suggest a 9-month childhood obesity intervention program was effective in improving the target health behaviors for a low-income Mexican American community and identifying effective means for reducing the incidence of obesity in high risks groups. A larger randomized control trial is needed to further test the feasibility of this intervention program

Personality-based recommendation: human curiosity applied to recommendation systems using implicit information from social networks

Tesis por compendioEn el día a día, las personas suelen confiar en recomendaciones, tradicionalmente aportadas por otras personas (familia, amigos, etc.) para sus decisiones más variadas. En el mundo digital esto no es diferente, dado que los sistemas de recomendación están presentes en todas partes y de modo transparente. El principal objetivo de estos sistemas es el de ayudar en el proceso de toma de decisiones, generando recomendaciones de su interés y basadas en sus gustos. Dichas recomendaciones van desde productos en sitios web de comercio electrónico, como libros o lugares a visitar, además de qué comer o cuánto tiempo uno debe caminar al día para tener una vida sana, con quién salir o a quién seguir en las redes sociales. Esta es un área en ascensión. Por un lado, tenemos cada vez más usuarios en internet cuya vida está digitalizada, dado que lo que se hace en el "mundo real" está representado en cierto modo en el "mundo digital". Por otro lado, sufrimos una sobrecarga de información, que puede mitigarse mediante el uso de un sistema de recomendación. Sin embargo, estos sistemas también enfrentan algunos problemas, como el problema del arranque en frío y su necesidad de ser cada vez más "humanos", "personalizados" y "precisos" para satisfacer las exigencias de usuarios y empresas. En este desafiante escenario, los sistemas de recomendación basados en la personalidad se están estudiando cada vez más, ya que son capaces de enfrentar esos problemas. Algunos proyectos recientes proponen el uso de la personalidad humana en los recomendadores, ya sea en su conjunto o individualmente por rasgos. Esta tesis está dedicada a este nuevo área de recomendación basada en la personalidad, centrándose en uno de sus rasgos más importantes, la curiosidad. Además, para explotar la información ya existente en internet, obtendremos de forma implícita información de las redes sociales. Por lo tanto, este trabajo tiene como objetivo proporcionar una mejor experiencia al usuario final a través de un nuevo enfoque que ofrece una alternativa a algunos de los retos identificados en los sistemas de recomendación basados en la personalidad. Entre estas mejoras, el uso de las redes sociales para alimentar los sistemas de recomendación reduce el problema del arranque en frío y, al mismo tiempo, proporciona datos valiosos para la predicción de la personalidad humana. Por otro lado, la curiosidad no ha sido utilizada por ninguno de los sistemas de recomendación estudiados; casi todos han usado la personalidad general de un individuo a través de los Cinco Grandes rasgos de la personalidad. Sin embargo, los estudios psicológicos confirman que la curiosidad es un rasgo relevante en el proceso de elegir un item, cuestión directamente relacionada con los sistemas de recomendación. En resumen, creemos que un sistema de recomendación que mida implícitamente la curiosidad y la utilice en el proceso de recomendar nuevos ítems, especialmente en el sector turístico, podría claramente mejorar la capacidad de estos sistemas en términos de precisión, serendipidad y novedad, permitiendo a los usuarios obtener niveles positivos de satisfacción con las recomendaciones. Esta tesis realiza un estudio exhaustivo del estado del arte, donde destacamos trabajos sobre sistemas de recomendación, la personalidad humana desde el punto de vista de la psicología tradicional y positiva y finalmente cómo se combinan ambos aspectos. Luego, desarrollamos una aplicación en línea capaz de extraer implícitamente información del perfil de usuario en una red social, generando predicciones de uno o más rasgos de su personalidad. Finalmente, desarrollamos el sistema CURUMIM, capaz de generar recomendaciones en línea con diferentes propiedades, combinando la curiosidad y algunas características sociodemográficas (como el nivel de educación) extraídas de Facebook. El sistema ha sido probado y evaluado en el contexto turístico por usuarios rEn el dia a dia, les persones solen confiar en recomanacions, tradicionalment aportades per altres persones (família, amics, etc.) per a les seues decisions més variades. En el món digital això no és diferent, atès que els sistemes de recomanació estan presents a tot arreu i de manera transparent. El principal objectiu d'aquests sistemes és el d'ajudar en el procés de presa de decisions, generant recomanacions del seu interès i basades en els seus gustos. Aquestes recomanacions van des de productes en pàgines web de comerç electrònic, com a llibres o llocs a visitar, a més de què menjar o quant temps una persona ha de caminar al dia per a tindre una vida sana, amb qui eixir o a qui seguir en les xarxes socials. Aquesta és una àrea en ascensió. D'una banda, tenim cada vegada més usuaris en internet la vida de les quals està digitalitzada, atès que el que es fa en el "món real" està representat en certa manera en el "món digital". D'altra banda, patim una sobrecàrrega d'informació, que pot mitigar-se mitjançant l'ús d'un sistema de recomanació. No obstant això, aquests sistemes també enfronten alguns problemes, com el problema de l'arrencada en fred i la seua necessitat de ser cada vegada més "humans", "personalitzats" i "precisos" per a satisfer les exigències d'usuaris i empreses. En aquest desafiador escenari, els sistemes de recomanació basats en la personalitat s'estan estudiant cada vegada més, ja que són capaços d'enfrontar eixos problemes. Alguns projectes recents proposen l'ús de la personalitat humana en els recomendadors, ja siga en el seu conjunt o individualment per trets. Aquesta tesi està dedicada a aquest nou àrea de recomanació basada en la personalitat, centrant-se en un dels seus trets més importants, la curiositat. A més, per a explotar la informació ja existent en internet, obtindrem de forma implícita informació de les xarxes socials. Per tant, aquest treball té com a objectiu proporcionar una millor experiència a l'usuari final a través d'un nou enfocament que ofereix una alternativa a alguns dels reptes identificats en els sistemes de recomanació basats en la personalitat. Entre aquestes millores, l'ús de les xarxes socials per a alimentar els sistemes de recomanació redueix el problema de l'arrencada en fred i, al mateix temps, proporciona dades valuoses per a la predicció de la personalitat humana. D'altra banda, la curiositat no ha sigut utilitzada per cap dels sistemes de recomanació estudiats; quasi tots han usat la personalitat general d'un individu a través dels Cinc Grans trets de la personalitat. No obstant això, els estudis psicològics confirmen que la curiositat és un tret rellevant en el procés de triar un item, qüestió directament relacionada amb els sistemes de recomanació. En resum, creiem que un sistema de recomanació que mesure implícitament la curiositat i la utilitze en el procés de recomanar nous ítems, especialment en el sector turístic, podria clarament millorar la capacitat d'aquests sistemes en termes de precisió, sorpresa i novetat, permetent als usuaris obtindre nivells positius de satisfacció amb les recomanacions. Aquesta tesi realitza un estudi exhaustiu de l'estat de l'art, on destaquem treballs sobre sistemes de recomanació, la personalitat humana des del punt de vista de la psicologia tradicional i positiva i finalment com es combinen tots dos aspectes. Després, desenvolupem una aplicació en línia capaç d'extraure implícitament informació del perfil d'usuari en una xarxa social, generant prediccions d'un o més trets de la seua personalitat. Finalment, desenvolupem el sistema CURUMIM, capaç de generar recomanacions en línia amb diferents propietats, combinant la curiositat i algunes característiques sociodemogràfiques (com el nivell d'educació) extretes de Facebook. El sistema ha sigut provat i avaluat en el context turístic per usuaris reals. Els resultats demostren la seua capacitat perIn daily life, people usually rely on recommendations, traditionally given by other people (family, friends, etc.) for their most varied decisions. In the digital world, this is not different, given that recommender systems are present everywhere in such a way that we no longer realize. The main goal of these systems is to assist users in the decision-making process, generating recommendations that are of their interest and based on their tastes. These recommendations range from products in e-commerce websites, like books to read or places to visit to what to eat or how long one should walk a day to have a healthy life, who to date or who one should follow on social networks. And this is an increasing area. On the one hand, we have more and more users on the internet whose life is somewhat digitized, given than what one does in the "real world" is represented in a certain way in the "digital world". On the other hand, we suffer from information overload, which can be mitigated by the use of recommendation systems. However, these systems also face some problems, such as the cold start problem and their need to be more and more "human", "personalised" and "precise" in order to meet the yearning of users and companies. In this challenging scenario, personality-based recommender systems are being increasingly studied, since they are able to face these problems. Some recent projects have proposed the use of the human personality in recommenders, whether as a whole or individually by facet in order to meet those demands. Therefore, this thesis is devoted to this new area of personality-based recommendation, focusing on one of its most important traits, the curiosity. Additionally, in order to exploit the information already present on the internet, we will implicitly obtain information from social networks. Thus, this work aims to build a better experience for the end user through a new approach that offers an option for some of the gaps identified in personality-based recommendation systems. Among these gap improvements, the use of social networks to feed the recommender systems soften the cold start problem and, at the same time, it provides valuable data for the prediction of the human personality. Another found gap is that the curiosity was not used by any of the studied recommender systems; almost all of them have used the overall personality of an individual through the Big Five personality traits. However, psychological studies confirm that the curiosity is a relevant trait in the process of choosing an item, which is directly related to recommendation systems. In summary, we believe that a recommendation system that implicitly measures the curiosity and uses it in the process of recommending new items, especially in the tourism sector, could clearly improve the capacity of these systems in terms of accuracy, serendipity and novelty, allowing users to obtain positive levels of satisfaction with the recommendations. This thesis begins with an exhaustive study of the state of the art, where we highlight works about recommender systems, the human personality from the point of view of traditional and positive psychology and how these aspects are combined. Then, we develop an online application capable of implicitly extracting information from the user profile in a social network, thus generating predictions of one or more personality traits. Finally, we develop the CURUMIM system, able to generate online recommendations with different properties, combining the curiosity and some sociodemographic characteristics (such as level of education) extracted from Facebook. The system is tested and assessed within the tourism context by real users. The results demonstrate its ability to generate novel and serendipitous recommendations, while maintaining a good level of accuracy, independently of the degree of curiosity of the users.Menk Dos Santos, A. (2018). Personality-based recommendation: human curiosity applied to recommendation systems using implicit information from social networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/114798TESISCompendi

Modern Socio-Technical Perspectives on Privacy

This open access book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy). The book is structured in four parts, which follow after an introduction to privacy on both a technical and social level: Privacy Theory and Methods covers a range of theoretical lenses through which one can view the concept of privacy. The chapters in this part relate to modern privacy phenomena, thus emphasizing its relevance to our digital, networked lives. Next, Domains covers a number of areas in which privacy concerns and implications are particularly salient, including among others social media, healthcare, smart cities, wearable IT, and trackers. The Audiences section then highlights audiences that have traditionally been ignored when creating privacy-preserving experiences: people from other (non-Western) cultures, people with accessibility needs, adolescents, and people who are underrepresented in terms of their race, class, gender or sexual identity, religion or some combination. Finally, the chapters in Moving Forward outline approaches to privacy that move beyond one-size-fits-all solutions, explore ethical considerations, and describe the regulatory landscape that governs privacy through laws and policies. Perhaps even more so than the other chapters in this book, these chapters are forward-looking by using current personalized, ethical and legal approaches as a starting point for re-conceptualizations of privacy to serve the modern technological landscape. The book’s primary goal is to inform IT students, researchers, and professionals about both the fundamentals of online privacy and the issues that are most pertinent to modern information systems. Lecturers or teacherscan assign (parts of) the book for a “professional issues” course. IT professionals may select chapters covering domains and audiences relevant to their field of work, as well as the Moving Forward chapters that cover ethical and legal aspects. Academicswho are interested in studying privacy or privacy-related topics will find a broad introduction in both technical and social aspects

Expanding market strategies for logon

This company project provides an analysis and evaluation of market expansion possibilities of the German company LogOn. The company offers an innovative and intuitive online matching technology originally designed for online recruiting in the field of human resources. Innovation plays an increasingly important role to be competitive in times of globalization, both in small businesses and general economic growth. Current success with the matching technology raises expansion plans into the area digital advertisement, focusing on an increasingly dramatic situation: on one hand digital advertising spend is constantly growing in Western Europe. On the other hand dissatisfaction with digital advertisement, by reason of low quality and clutter is simultaneously increasing. As a matter of fact advertising is getting less effective. Linking the current situation of digital advertising with the concept of Innovation Management, a new challenge and market expansion into digital advertisement appears possible: can LogOn’s online matching technology expands into the field of digital and media advertising in order to create added value? Following the framework of Innovation Process, the idea generation process delivers a concrete product idea. The matching technology is able to intuitively create a profile of a user. It looks at the motivation of information, estimates possible consequences and generates additional information intuitively. The matching technology serves as an intelligent spam filter, which is able to exclude irrelevant content from a user’s mobile or desktop device. The technology offers a better customer experience and increases customer satisfaction. This benefit can be used in the B2C and B2B sector by offering users a more enjoyable advertisement experience and adding value by making advertisement more effective and successful in general. LogOn´s matching technology has three target groups: users, publisher and vendors

Net Neutrality

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. Chris Marsden maneuvers through the hype articulated by Netwrok Neutrality advocates and opponents. He offers a clear-headed analysis of the high stakes in this debate about the Internet's future, and fearlessly refutes the misinformation and misconceptions that about' Professor Rob Freiden, Penn State University Net Neutrality is a very heated and contested policy principle regarding access for content providers to the Internet end-user, and potential discrimination in that access where the end-user's ISP (or another ISP) blocks that access in part or whole. The suggestion has been that the problem can be resolved by either introducing greater competition, or closely policing conditions for vertically integrated service, such as VOIP. However, that is not the whole story, and ISPs as a whole have incentives to discriminate between content for matters such as network management of spam, to secure and maintain customer experience at current levels, and for economic benefit from new Quality of Service standards. This includes offering a ‘priority lane' on the network for premium content types such as video and voice service. The author considers market developments and policy responses in Europe and the United States, draws conclusions and proposes regulatory recommendations

Next Generation Access in a Rural Community Context: An Innovation Analysis

This thesis explores how to resolve the digital divide in Wales. This is important because access to advanced broadband is considered an essential requirement, particularly post-COVID19. UK Government is advocating next generation access (NGA) to capitalise on Industry 4.0. However, the financial costs and complexities of connecting the final few rural areas is a persisting problem area. Hence, this thesis explores new innovative approaches to provide NGA (product) to a final few (market). Studies revealed superfast broadband in remote rural communities has four-fold human, social, environmental and financial capital benefits. Analysis resulted in a new conceptual framework which combines neo-endogenous theories alongside a four-fold capital model to characterise the complex ecosystem. Previous literature focused on either supply or demand, but few studies had investigated both together at the local level. Human & social capital were identified as critical success factors in community-led initiatives, thus providing a theoretical underpinning for this thesis. This study employed a novel mutual business approach utilising the Hybrid Value System (HVS) as an ecosystem connecting the core assets of several stakeholders. Furthermore, the World Bank Social Capital Assessment Tool was modified to investigate social capital fertility to enhance investment. Henceforth, a qualitative multi-method and in-depth intrinsic case study was used to explore the ecosystem. The contribution to knowledge is how to engage multi-stakeholder and multi-capital analysis to resolve the problem area. The results identified human capital productivity, social capital collective action, and shared financial capital are required at the local level to reach the final few. The mutual business paradigm challenges all stakeholders to value non-financial capital alongside financial capital for problem area resolution. This thesis concludes that HVS methodology coupled with complex ecosystem-network visualisation techniques, provide academics, management and government policy makers with practical tools to value four-fold capital resources and bridge the digital divide