DOBBS: Towards a Comprehensive Dataset to Study the Browsing Behavior of Online Users

The investigation of the browsing behavior of users provides useful information to optimize web site design, web browser design, search engines offerings, and online advertisement. This has been a topic of active research since the Web started and a large body of work exists. However, new online services as well as advances in Web and mobile technologies clearly changed the meaning behind "browsing the Web" and require a fresh look at the problem and research, specifically in respect to whether the used models are still appropriate. Platforms such as YouTube, Netflix or last.fm have started to replace the traditional media channels (cinema, television, radio) and media distribution formats (CD, DVD, Blu-ray). Social networks (e.g., Facebook) and platforms for browser games attracted whole new, particularly less tech-savvy audiences. Furthermore, advances in mobile technologies and devices made browsing "on-the-move" the norm and changed the user behavior as in the mobile case browsing is often being influenced by the user's location and context in the physical world. Commonly used datasets, such as web server access logs or search engines transaction logs, are inherently not capable of capturing the browsing behavior of users in all these facets. DOBBS (DERI Online Behavior Study) is an effort to create such a dataset in a non-intrusive, completely anonymous and privacy-preserving way. To this end, DOBBS provides a browser add-on that users can install, which keeps track of their browsing behavior (e.g., how much time they spent on the Web, how long they stay on a website, how often they visit a website, how they use their browser, etc.). In this paper, we outline the motivation behind DOBBS, describe the add-on and captured data in detail, and present some first results to highlight the strengths of DOBBS

Online multitasking and user engagement

Users often access and re-access more than one site during an online session, effectively engaging in multitasking. In this paper, we study the effect of online multitasking on two widely used engagement metrics designed to capture users browsing behavior with a site. Our study is based on browsing data of 2.5M users across 760 sites encompass-ing diverse types of services such as social media, news and mail. To account for multitasking we need to redefine how user sessions are represented and we need to adapt the met-rics under study. We introduce a new representation of user sessions: tree-streams – as opposed to the commonly used click-streams – present a more accurate picture of the brows-ing behavior of a user that includes how users switch between sites (e.g., hyperlinking, teleporting, backpaging). We then discuss a number of insights on multitasking patterns, and show how these help to better understand how users engage with sites. Finally, we define metrics that characterize mul-titasking during online sessions and show how they provide additional insights to standard engagement metrics

Off the Beaten tracks: Exploring Three Aspects of Web Navigation

This paper presents results of a long-term client-side Web usage study, updating previous studies that range in age from five to ten years. We focus on three aspects of Web navigation: changes in the distribution of navigation actions, speed of navigation and within-page navigation. “Navigation actions” corresponding to users’ individual page requests are discussed by type. We reconfirm links to be the most important navigation element, while backtracking has lost more than half of its previously reported share and form submission has become far more common. Changes of the Web and the browser interfaces are candidates for causing these changes. Analyzing the time users stayed on pages, we confirm Web navigation to be a rapidly interactive activity. A breakdown of page characteristics shows that users often do not take the time to read the available text or consider all links. The performance of the Web is analyzed and reassessed against the resulting requirements. Finally, habits of within-page navigation are presented. Although most selected hyperlinks are located in the top left corner of the screen, in nearly a quarter of all cases people choose links that require scrolling. We analyzed the available browser real estate to gain insights for the design of non-scrolling Web pages

Revisitation analysis of smartphone app use

We present a revisitation analysis of smartphone use to investigate the question: do smartphones induce usage habits? We analysed three months of application launch logs from 165 users in naturalistic settings. Our analysis reveals distinct clusters of applications and users which share similar revisitation patterns. However, we show that much of smartphone usage on a macro-level is very similar to web browsing on desktops, and thus argue that smartphone usage is driven by innate service needs rather than technology characteristics. On the other hand, on a micro-level we identify unique characteristics in smartphone usage, and we present a rudimentary model that accounts for 92 % in the variability of our smartphone use. Author Keywords Revisitation, smartphone use, habits, user behaviou

Diverse Contributions to Implicit Human-Computer Interaction

Cuando las personas interactúan con los ordenadores, hay mucha información que no se proporciona a propósito. Mediante el estudio de estas interacciones implícitas es posible entender qué características de la interfaz de usuario son beneficiosas (o no), derivando así en implicaciones para el diseño de futuros sistemas interactivos. La principal ventaja de aprovechar datos implícitos del usuario en aplicaciones informáticas es que cualquier interacción con el sistema puede contribuir a mejorar su utilidad. Además, dichos datos eliminan el coste de tener que interrumpir al usuario para que envíe información explícitamente sobre un tema que en principio no tiene por qué guardar relación con la intención de utilizar el sistema. Por el contrario, en ocasiones las interacciones implícitas no proporcionan datos claros y concretos. Por ello, hay que prestar especial atención a la manera de gestionar esta fuente de información. El propósito de esta investigación es doble: 1) aplicar una nueva visión tanto al diseño como al desarrollo de aplicaciones que puedan reaccionar consecuentemente a las interacciones implícitas del usuario, y 2) proporcionar una serie de metodologías para la evaluación de dichos sistemas interactivos. Cinco escenarios sirven para ilustrar la viabilidad y la adecuación del marco de trabajo de la tesis. Resultados empíricos con usuarios reales demuestran que aprovechar la interacción implícita es un medio tanto adecuado como conveniente para mejorar de múltiples maneras los sistemas interactivos.Leiva Torres, LA. (2012). Diverse Contributions to Implicit Human-Computer Interaction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17803Palanci

You are here: Building an online interactive map application

As new map applications have increased in popularity the opportunities for gathering geographic data have increased as well. The difficulty that interactive user-driven map applications have is the motivation for user participation. People have become more comfortable contributing to forums, blogs, and sites driven by user content, but user-driven map sites have been slow to cultivate a large amount of user-contributed data. Focusing on a small geographic area can increase user participation within interactive map applications. The design and implementation of an online map applications focused on a small geographic area is presented. The site uses a map interface to gather new spatial data from users, as well as allowing browsing and search. Users can also annotate existing data on the site through the map interface. The final site presents a mix between theory-based design and the inherent limitations of a practical implementation

Use of Landmarks to Improve Spatial Learning and Revisitation in Computer Interfaces

Efficient spatial location learning and remembering are just as important for two-dimensional Graphical User Interfaces (GUI) as they are for real environments where locations are revisited multiple times. Rapid spatial memory development in GUIs, however, can be difficult because these interfaces often lack adequate landmarks that have been predominantly used by people to learn and recall real-life locations. In the absence of sufficient landmarks in GUIs, artificially created visual objects (i.e., artificial landmarks) could be used as landmarks to support spatial memory development of spatial locations. In order to understand how spatial memory development occurs in GUIs and explore ways to assist users’ efficient location learning and recalling in GUIs, I carried out five studies exploring the use of landmarks in GUIs – one study that investigated interfaces of four standard desktop applications: Microsoft Word, Facebook, Adobe Photoshop, and Adobe Reader, and other four that tested artificial landmarks augmented two prototype desktop GUIs against non-landmarked versions: command selection interfaces and linear document viewers; in addition, I tested landmarks’ use in variants of these interfaces that varied in the number of command sets (small, medium, and large) and types of linear documents (textual and video). Results indicate that GUIs’ existing features and design elements can be reliable landmarks in GUIs that provide spatial benefits similar to real environments. I also show that artificial landmarks can significantly improve spatial memory development of GUIs, allowing support for rapid spatial location learning and remembering in GUIs. Overall, this dissertation reveals that landmarks can be a valuable addition to graphical systems to improve the memorability and usability of GUIs

Interest identification from browser tab titles: A systematic literature review

Modeling and understanding users interests has become an essential part of our daily lives. A variety of business processes and a growing number of companies employ various tools to such an end. The outcomes of these identification strategies are beneficial for both companies and users: the former are more likely to offer services to those customers who really need them, while the latter are more likely to get the service they desire. Several works have been carried out in the area of user interests identification. As a result, it might not be easy for researchers, developers, and users to orient themselves in the field; that is, to find the tools and methods that they most need, to identify ripe areas for further investigations, and to propose the development and adoption of new research plans. In this study, to overcome these potential shortcomings, we performed a systematic literature review on user interests identification. We used as input data browsing tab titles. Our goal here is to offer a service to the readership, which is capable of systematically guiding and reliably orienting researchers, developers, and users in this very vast domain. Our findings demonstrate that the majority of the research carried out in the field gathers data from either social networks (such as Twitter, Instagram and Facebook) or from search engines, leaving open the question of what to do when such data is not available