Exploring the information behaviour of users of Welsh Newspapers Online through web log analysis

Purpose – Webometric techniques have been applied to many websites and online resources, especially since the launch of Google Analytics (GA). To date, though, there has been little consideration of information behaviour in relation to digitised newspaper collections. The purpose of this paper is to address a perceived gap in the literature by providing an account of user behaviour in the newly launched Welsh Newspapers Online (WNO). Design/methodology/approach – The author collected webometric data for WNO using GA and web server content logs. These were analysed to identify patterns of engagement and user behaviour, which were then considered in relation to existing information behaviour. Findings – Use of WNO, while reminiscent of archival information seeking, can be understood as centring on the web interface rather than the digitised material. In comparison to general web browsing, users are much more deeply engaged with the resource. This engagement incorporates reading online, but users’ information seeking utilises website search and browsing functionality rather than filtering in newspaper material. Information seeking in digitised newspapers resembles the model of the “user” more closely than that of the “reader”, a value-laden distinction which needs further unpacking. Research limitations/implications – While the behaviour discussed in this paper is likely to be more widely representative, a larger longitudinal data set would increase the study’s significance. Additionally, the methodology of this paper can only tell us what users are doing, and further research is needed to identify the drivers for this behaviour. Originality/value – This study provides important insights into the underinvestigated area of digitised newspaper collections, and shows the importance of webometric methods in analysing online user behaviour

Daily Stress Recognition from Mobile Phone Data, Weather Conditions and Individual Traits

Research has proven that stress reduces quality of life and causes many diseases. For this reason, several researchers devised stress detection systems based on physiological parameters. However, these systems require that obtrusive sensors are continuously carried by the user. In our paper, we propose an alternative approach providing evidence that daily stress can be reliably recognized based on behavioral metrics, derived from the user's mobile phone activity and from additional indicators, such as the weather conditions (data pertaining to transitory properties of the environment) and the personality traits (data concerning permanent dispositions of individuals). Our multifactorial statistical model, which is person-independent, obtains the accuracy score of 72.28% for a 2-class daily stress recognition problem. The model is efficient to implement for most of multimedia applications due to highly reduced low-dimensional feature space (32d). Moreover, we identify and discuss the indicators which have strong predictive power.Comment: ACM Multimedia 2014, November 3-7, 2014, Orlando, Florida, US

Mobile Consumer Behavior in Fashion m-Retail: An Eye Tracking Study to Understand Gender Differences

© 2020 ACM. With exponential adoption of mobile devices, consumers increasingly use them for shopping. There is a need to understand the gender differences in mobile consumer behavior. This study used mobile eye tracking technology and mixed-method approach to analyze and compare how male and female mobile fashion consumers browse and shop on smartphones. Mobile eye tracking glasses recorded fashion consumers' shopping experiences using smartphones for browsing and shopping on the actual fashion retailer's website. 14 participants successfully completed this study, half of them were males and half females. Two different data analysis approaches were employed, namely a novel framework of the shopping journey, and semantic gaze mapping with 31 Areas of Interest (AOI) representing the elements of the shopping journey. The results showed that male and female users exhibited significantly different behavior patterns, which have implications for mobile website design and fashion m-retail. The shopping journey map framework proves useful for further application in market research

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

Supporting Location Privacy Management through Feedback and Control

Participation in modern, socially-focused digital systems involves a large degree of privacy management, i.e. controlling who may access what information under what circumstances. Effective privacy management (control) requires that mobile systems’ users be able to make informed privacy decisions as their experience and knowledge of a system progresses. By informed, we mean users be aware of the actual information flow. Moreover, privacy preferences vary across the context and it is hard to define privacy policy that reflects the dynamic nature of our lives. This research explores the problem of supporting awareness of information flow and designing usable interfaces for maintaining privacy policies ad-hoc. We borrow from the world of Computer Supported Collaborative Work (CSCW) and propose to incorporate social translucence, a design approach that “supports coherent behaviour by making participants and their activities visible to one another”. We use the characteristics of social translucence, namely visibility, awareness and accountability in order to introduce social norms in spatially dispersed systems. Our research is driven by two questions: (1) how can artifacts from real world social interaction, such as responsibility, be embedded into mobile interaction; and (2) can systems be designed in which both privacy violations and the burden of privacy management is minimized. The contributions of our work are: (1) an implementation of Buddy Tracker, privacy-aware location-sharing application based on the social translucence; (2) the design and evaluation of the concept of real-time feedback as a means of incorporating social translucence in location-sharing scenarios; and finally (3) a novel interface for ad-hoc privacy management called Privacy-Shake. We explore the role of real-time feedback for privacy management in the context of Buddy Tracker. Informed by focus group discussions, interviews, surveys and two field trials of Buddy Tracker we found that when using a system that provided real-time feedback, people were more accountable for their actions and reduced the number of unreasonable location requests. From our observations we develop concrete design guidelines for incorporating real-time feedback into information sharing applications in a manner that ensures social acceptance of the technology

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Description and application of the correlation between gaze and hand for the different hand events occurring during interaction with tablets

People’s activities naturally involve the coordination of gaze and hand. Research in Human-Computer Interaction (HCI) endeavours to enable users to exploit this multimodality for enhanced interaction. With the abundance of touch screen devices, direct manipulation of an interface has become a dominating interaction technique. Although touch enabled devices are prolific in both public and private spaces, interactions with these devices do not fully utilise the benefits from the correlation between gaze and hand. Touch enabled devices do not employ the richness of the continuous manual activity above their display surface for interaction and a lot of information expressed by users through their hand movements is ignored. This thesis aims at investigating the correlation between gaze and hand during natural interaction with touch enabled devices to address these issues. To do so, we set three objectives. Firstly, we seek to describe the correlation between gaze and hand in order to understand how they operate together: what is the spatial and temporal relationship between these modalities when users interact with touch enabled devices? Secondly, we want to know the role of some of the inherent factors brought by the interaction with touch enabled devices on the correlation between gaze and hand, because identifying what modulates the correlation is crucial to design more efficient applications: what are the impacts of the individual differences, the task characteristics and the features of the on-screen targets? Thirdly, as we want to see whether additional information related to the user can be extracted from the correlation between gaze and hand, we investigate the latter for the detection of users’ cognitive state while they interact with touch enabled devices: can the correlation reveal the users’ hesitation? To meet the objectives, we devised two data collections for gaze and hand. In the first data collection, we cover the manual interaction on-screen. In the second data collection, we focus instead on the manual interaction in-the-air. We dissect the correlation between gaze and hand using three common hand events users perform while interacting with touch enabled devices. These events comprise taps, stationary hand events and the motion between taps and stationary hand events. We use a tablet as a touch enabled device because of its medium size and the ease to integrate both eye and hand tracking sensors. We study the correlation between gaze and hand for tap events by collecting gaze estimation data and taps on tablet in the context of Internet related tasks, representative of typical activities executed using tablets. The correlation is described in the spatial and temporal dimensions. Individual differences and effects of the task nature and target type are also investigated. To study the correlation between gaze and hand when the hand is in a stationary situation, we conducted a data collection in the context of a Memory Game, chosen to generate enough cognitive load during playing while requiring the hand to leave the tablet’s surface. We introduce and evaluate three detection algorithms, inspired by eye tracking, based on the analogy between gaze and hand patterns. Afterwards, spatial comparisons between gaze and hands are analysed to describe the correlation. We study the effects on the task difficulty and how the hesitation of the participants influences the correlation. Since there is no certain way of knowing when a participant hesitates, we approximate the hesitation with the failure of matching a pair of already seen tiles. We study the correlation between gaze and hand during hand motion between taps and stationary hand events from the same data collection context than the case mentioned above. We first align gaze and hand data in time and report the correlation coefficients in both X and Y axis. After considering the general case, we examine the impact of the different factors implicated in the context: participants, task difficulty, duration and type of the hand motion. Our results show that the correlation between gaze and hand, throughout the interaction, is stronger in the horizontal dimension of the tablet rather than in its vertical dimension, and that it varies widely across users, especially spatially. We also confirm the eyes lead the hand for target acquisition. Moreover, we find out that the correlation between gaze and hand when the hand is in the air above the tablet’s surface depends on where the users look at on the tablet. As well, we show that the correlation during eye and hand during stationary hand events can indicate the users’ indecision, and that while the hand is moving, the correlation depends on different factors, such as the degree of difficulty of the task performed on the tablet and the nature of the event before/after the motion

From user browsing behaviour to user demographics

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementA Internet conta hoje com mais de 3 mil milhões de utilizadores e esse valor não para de aumentar. Desta forma, proporcionar uma experiência online agradável aos seus utilizadores é cada vez mais importante para as empresas. De modo a tirar partido dos benefícios deste crescimento, as empresas devem ser capazes de identificar os seus clientes-alvo dentro do total de utilizadores; e, subsequentemente, personalizar a sua experiência online. Existem diversas formas de estudar o comportamento online dos utilizadores; no entanto, estas não são ideais e existe uma ampla margem para melhoria. A inovação nesta área pode comportar um grande potencial comercial e até ser disruptiva. Com isto em mente, proponho-me a estudar a possível criacão de um sistema de aprendizagem automática (machine learning) que permita prever informa ações demográficas dos utilizadores estritamente com base no seu comportamento online. Tal sistema poderia constituir uma alternativa às atuais opções, que são mais invasivas; mitigando assim preocupações ao nível da proteção de dados pessoais. No primeiro capítulo (Introdução) explico a motivação para o estudo do comportamento dos utilizadores online por parte de empresas, e descrevo as opções disponíveis atualmente. Apresento também a minha proposta e o contexto em que assenta. O capítulo termina com a identicação de limitações que possam existir a priori. O segundo capítulo (Machine Learning) fornece uma introdução sobre machine learning, com o estudo dos algoritmos que vão ser utilizados e explicando como analisar os resultados. O terceiro capítulo (Implementação) explica a implementação do sistema proposto e descreve o sistema que desenvolvi no decorrer deste estudo, e como integra-lo em sistemas já existentes. No quarto capítulo (Análise e manipulação dos dados), mostro os dados compilados e explico como os recolhi e manipulei para testar a hipótese. No quinto capítulo (Análise de dados e discussão) vemos como e que os dados recolhidos foram usados pelos vários algoritmos para descobrir como se correlacionam com dados dos utilizadores e analiso e discuto os resultados observados. Por fim, o sexto e último capítulo apresenta as conclusões. Dependendo dos resultados, mostro como a hipótese poderia ser melhor testada, ou então discuto os próximos passos para tornar o sistema realidade

Research methods on the Internet

This chapter considers how the various internet communication technologies discussed in Section I can and have been used to support, and arguably transform, social and behavioural research methods. Focus here is on primary research, that is, "the acquisition and analysis of data to produce novel evidence and research findings" (Hewson, Laurent and Vogel, forthcoming). Primary research on the internet has been referred to as internet-mediated research (IMR) (Hewson et al. 2003) and this term will be adopted throughout the present chapter. The chapter will not consider secondary research on the internet, such as conducting a literature review or creating a bibliography; for useful guides on the latter see Hewson et al. (2003); Ó Dochartaigh (2012). The structure of the chapter is as follows: overview and history of IMR; scope and range of IMR methods, with illustrations; key issues and debates in IMR (data quality, sampling, ethics); future possibilities and directions

A design space for social object labels in museums

Taking a problematic user experience with ubiquitous annotation as its point of departure, this thesis defines and explores the design space for Social Object Labels (SOLs), small interactive displays aiming to support users' in-situ engagement with digital annotations of physical objects and places by providing up-to-date information before, during and after interaction. While the concept of ubiquitous annotation has potential applications in a wide range of domains, the research focuses in particular on SOLs in a museum context, where they can support the institution's educational goals by engaging visitors in the interpretation of exhibits and providing a platform for public discourse to complement official interpretations provided on traditional object labels. The thesis defines and structures the design space for SOLs, investigates how they can support social interpretation in museums and develops empirically validated design recommendations. Reflecting the developmental character of the research, it employs Design Research as a methodological framework, which involves the iterative development and evaluation of design artefacts together with users and other stakeholders. The research identifies the particular characteristics of SOLs and structures their design space into ten high-level aspects, synthesised from taxonomies and heuristics for similar display concepts and complemented with aspects emerging from the iterative design and evaluation of prototypes. It presents findings from a survey exploring visitors' mental models, preferences and expectations of commenting in museums and translates them into requirements for SOLs. It reports on scenario-based design activities, expert interviews with museum professionals, formative user studies and co-design sessions, and two empirical evaluations of SOL prototypes in a gallery environment. Pulling together findings from these research activities it then formulates design recommendations for SOLs and supports them with related evidence and implementation examples. The main contributions are (i) to delineate and structure the design space for SOLs, which helps to ground SOLs in the literature and understand them as a distinct display concept with its own characteristics; (ii) to explore, for the first time, a visitor perspective on commenting in museums, which can inform research, development and policies on user-generated content in museums and the wider cultural heritage sector; (iii) to develop empirically validated design recommendations, which can inform future research and development into SOLs and related display concept. The thesis concludes by summarising findings in relation to its stated research questions, restating its contributions from ubiquitous computing, domain and methodology perspectives, and discussing open issues and future work