174 research outputs found

    Responsive and Personalized Web Layouts with Integer Programming

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    Over the past decade, responsive web design (RWD) has become the de facto standard for adapting web pages to a wide range of devices used for browsing. While RWD has improved the usability of web pages, it is not without drawbacks and limitations: designers and developers must manually design the web layouts for multiple screen sizes and implement associated adaptation rules, and its "one responsive design fits all"approach lacks support for personalization. This paper presents a novel approach for automated generation of responsive and personalized web layouts. Given an existing web page design and preferences related to design objectives, our integer programming -based optimizer generates a consistent set of web designs. Where relevant data is available, these can be further automatically personalized for the user and browsing device. The paper includes presentation of techniques for runtime adaptation of the designs generated into a fully responsive grid layout for web browsing. Results from our ratings-based online studies with end users (N = 86) and designers (N = 64) show that the proposed approach can automatically create high-quality responsive web layouts for a variety of real-world websites.Peer reviewe

    Performance of online advertising : search, display and social media Ads

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    Digital advertising is becoming increasingly relevant. In particular, managers are gradually allocating the online budget to mobile and social media advertising. For that reason, it becomes essential to understand the performance of different ad types and the dynamics within each format and platform. The present study aims to compare different ad types – search, display and social media – whilst assessing the impact of different devices – mobile devices and computers – on online campaign performance. Moreover, it seeks to understand the factors that explain the performance within each ad type. This dissertation focuses on a B2B company that advertises an invoicing software using Google and Facebook. To this end, the study is based on descriptive quantitative research, analyzing secondary data from sixteen campaigns. The results show that search ads perform better on average than social media and display ads. However, the device of impression has also a significant impact on campaign performance. In fact, ads displayed on mobile devices yield more clicks and ads displayed on computer desktops generate more conversions. On Facebook, users often clicked on an ad in a mobile device and switched to a computer to convert. Besides, the targeting strategy adopted in display and social media ads has a significant influence on performance. On social media, ads retargeted to visitors of the company’s website originated significantly more conversions. In conclusion, these findings are relevant for managers in allocating the online budget across ad types and in optimizing the ads for different devices and target audience.A publicidade digital tem um peso crescente na despesa em publicidade. Em particular, as empresas estão a alocar o orçamento digital a publicidade móvel e nas redes sociais. É essencial compreender o desempenho de diferentes tipos de anúncios e a dinâmica dentro de cada tipo de formato e de plataforma. O presente estudo compara diferentes tipos de anúncios – anúncios de pesquisa, de display e de redes sociais – analisando o impacto dos dispositivos de exibição – dispositivos móveis e computadores – no desempenho de campanhas. Além disso, pretende identificar os factores explicativos do desempenho de cada tipo de anúncio. A dissertação foca-se numa empresa comercial que anuncia um software de facturação através do Google e do Facebook. Numa óptica de pesquisa quantitativa descritiva, este estudo analisa dados secundários de dezasseis campanhas. Os resultados mostram que os anúncios de pesquisa têm em média um melhor desempenho. Contudo, o dispositivo de impressão tem uma influência significativa no mesmo. Os anúncios exibidos em dispositivos móveis geraram mais cliques e os anúncios exibidos em computadores mais conversões. No Facebook, alguns utilizadores clicaram no anúncio através de um dispositivo móvel e subscreveram ao software num computador. Adicionalmente, a estratégia de segmentação adoptada nos anúncios display e nas redes sociais influenciou o seu desempenho. No Facebook, os anúncios redireccionados aos visitantes do site da empresa originaram significativamente mais conversões. Concluindo, estes resultados são relevantes na alocação do orçamento digital a vários tipos de anúncios e na optimização dos anúncios para diferentes dispositivos e tipos de público alvo

    SMIL State: an architecture and implementation for adaptive time-based web applications

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    In this paper we examine adaptive time-based web applications (or presentations). These are interactive presentations where time dictates which parts of the application are presented (providing the major structuring paradigm), and that require interactivity and other dynamic adaptation. We investigate the current technologies available to create such presentations and their shortcomings, and suggest a mechanism for addressing these shortcomings. This mechanism, SMIL State, can be used to add user-defined state to declarative time-based languages such as SMIL or SVG animation, thereby enabling the author to create control flows that are difficult to realize within the temporal containment model of the host languages. In addition, SMIL State can be used as a bridging mechanism between languages, enabling easy integration of external components into the web application. Finally, SMIL State enables richer expressions for content control. This paper defines SMIL State in terms of an introductory example, followed by a detailed specification of the State model. Next, the implementation of this model is discussed. We conclude with a set of potential use cases, including dynamic content adaptation and delayed insertion of custom content such as advertisements. © 2009 Springer Science+Business Media, LLC

    Cascading Tree Sheets and recombinant HTML: Better encapsulation and retargeting of web content

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    Cascading Style Sheets (CSS) took a valuable step towards separating web content from presentation. But HTML pages still contain large amounts of "design scaffolding" needed to hierarchically layer content for proper presentation. This paper presents Cascading Tree Sheets (CTS), a CSS-like language for separating this presentational HTML from real content. With CTS, authors can use standard CSS selectors to describe how to graft presentational scaffolding onto their pure-content HTML. This improved separation of content from presentation enables even naive authors to incorporate rich layouts (including interactive Javascript) into their own pages simply by linking to a tree sheet and adding some class names to their HTML

    Modern Practices for Responsive Web Design and Web Accessibility

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    Responsive web design and web accessibility play crucial roles in ensuring an optimal user experience on the web. By designing websites with responsiveness and accessibility in mind, more opportunities are opened up for a wider audience to access and interact with our content. Through modern practices, responsive web design allows websites to reach several different devices ranging from compact smartwatches to expansive television screens. Designing for accessibility provides accommodations for individuals with impairments while also providing benefits for individuals without impairments. However, designing for responsiveness and accessibility can present challenges; a poor attempt at providing accessibility features can worsen a user’s experience. It is vital that a website is designed properly to ensure usability for all users

    Reining in the Big Promise of Big Data: Transparency, Inequality, and New Regulatory Frontiers

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    The growing differentiation of services based on Big Data harbors the potential for both greater societal inequality and for greater equality. Anti-discrimination law and transparency alone, however, cannot do the job of curbing Big Data’s negative externalities while fostering its positive effects. To rein in Big Data’s potential, we adapt regulatory strategies from behavioral economics, contracts and criminal law theory. Four instruments stand out: First, active choice may be mandated between data collecting-services (paid by data) and data-free services (paid by money). Our suggestion provides concrete estimates for the price range of a data-free option, sheds new light on the monetization of data-collecting services, and proposes an “inverse predatory pricing” instrument to limit excessive pricing of the data-free option. Second, we propose using the doctrine of unconscionability to prevent contracts that unreasonably favor data-collecting companies. Third, we suggest democratizing data collection by regular user surveys and data compliance officers partially elected by users. Finally, we trace back new Big Data personalization techniques to the old Hartian precept of treating like cases alike and different cases – differently. If it is true that a speeding ticket over $50 is less of a disutility for a millionaire than for a welfare recipient, the income and wealth-responsive fines powered by Big Data that we suggest offer a glimpse into the future of the mitigation of economic and legal inequality by personalized law. Throughout these different strategies, we show how salience of data collection can be coupled with attempts to prevent discrimination and exploitation of users. Finally, we discuss all four proposals in the context of different test cases: social media, student education software and credit and cell phone markets. Many more examples could and should be discussed. In the face of increasing unease about the asymmetry of power between Big Data collectors and dispersed users, about differential legal treatment, and about the unprecedented dimensions of economic inequality, this paper proposes a new regulatory framework and research agenda to put the powerful engine of Big Data to the benefit of both the individual and societies adhering to basic notions of equality and non-discrimination

    The Economics of Internet Media

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    We survey the economics literature on media as it applies to the Internet. The Internet is an important driver behind media convergence and connects information and communication technologies. While new Internet media share some properties with traditional media, several novel features have appeared: On the content side, aggregation by third parties that have no editorial policy and user-generated content have become increasingly important. On the advertiser side, fine-tuned tailoring and targeting of ads based on individual user characteristics are common features on many Internet media and social networks. On the user side, we observe increased possibilities of time-shifting, multi-homing, and active search. These changes have gone hand-in-hand with new players entering media markets, including search engines and Internet service providers. Some of these players face novel strategic considerations, such as how to present search results. In response to these changes, an emerging economics literature focuses on the allocative and welfare implications of this new media landscape. This paper is an attempt to organize these contributions and provide a selective account of novel economic mechanisms that shape market outcomes of Internet media. A large body of work has focused on the advertising part of the industry, while some studies also look at content provision and the interaction between the two

    A Proposal Digital Marketing Strategy for Marcheluzzo Srl: Training and Evaluating a Prediction Model for the Number of Adv. Impressions

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    This research aims to describe a digital marketing strategy elaborated to be deployed in the MarcheluzzoSrl Company located in Italy. In addition, it intends to give a wide range of information to the company about its customers, target, competitors, market, digital marketing strategy, and potential recommendations. It is also important to highlight that this strategy is focused on the Brazilian market. Most of the information collected for the situational analysis and many other components for this research were gathered through the author`s perception during his internship in the company. The methodology includes secondary data collected through field observation in the company, documents provided by the organization and internet sources. Finally, the proposal digital marketing strategy was validated through a prediction model using machine-learning system via Python and its tools. The result of the prediction model was addressed and analyzed based on linear regression and correlation matrix methods confirming the efficacy of the proposal strategy, consequently the reliability of the prediction model
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