Showing papers by "Pamela Briggs published in 2015"

Nudging towards security: developing an application for wireless network selection for android phones

Abstract: People make security choices on a daily basis without fully considering the security implications of those choices. In this paper we present a prototype application which promotes the choice of secure wireless network options, specifically when users are unfamiliar with the wireless networks available. The app was developed based on behavioural theory, choice architecture and good practices informed by HCI design. The app includes several options to 'nudge' users towards selecting more secure public wireless networks. This paper outlines the development and the results of an evaluation of some of the potential app nudges (specifically, presentation order and colour coding). Colour coding was found to be a powerful influence, less so with the order in which we listed the Wi-Fi networks, although the colour x order combination was most effective. The paper contributes to the body of evidence on the effectiveness of cyber-security interventions to empower the user to make more informed security decisions.

An Inclusive, Value Sensitive Design Perspective on Future Identity Technologies

Abstract: Identity technologies constitute one of the fastest growing areas for research and development, driven by both commercial and administrative imperatives. Crucially, they constitute the means by which we include or exclude individuals and groups in terms of access to goods, services or information -- yet few developments in this space embrace an inclusive or value sensitive design philosophy. We describe a rigorous exercise in which we source scenarios that capture new research in the identity space and use these as probes in an inclusive design process. Workshops were held with six marginalized community groups: young people, older adults, refugees, black minority ethnic (BME) women, people with disabilities, and mental health service users. Our findings echo Herzberg's two-factor theory in which we are able to identify a set of relatively common values around sources of potential dissatisfaction (hygiene factors) as well as a set of motivators that are differentially valued across communities.

Identifying Prominent Life Events on Twitter

Abstract: Social media is a common place for people to post and share digital reflections of their life events, including major events such as getting married, having children, graduating, etc. Although the creation of such posts is straightforward, the identification of events on online media remains a challenge. Much research in recent years focused on extracting major events from Twitter, such as earthquakes, storms, and floods. This paper however, targets the automatic detection of personal life events, focusing on five events that psychologists found to be the most prominent in people lives. We define a variety of features (user, content, semantic and interaction) to capture the characteristics of those life events and present the results of several classification methods to automatically identify these events in Twitter. Our proposed classification methods obtain results between 0.84 and 0.92 F1-measure for the different types of life events. A novel contribution of this work also lies in a new corpus of tweets, which has been annotated by using crowdsourcing and that constitutes, to the best of our knowledge, the first publicly available dataset for the automatic identification of personal life events from Twitter.

How to Drive a London Bus: Measuring Performance in a Mobile and Remote Workplace

Abstract: This paper examines how London bus drivers have responded to performance monitoring via a telematics device called Drivewell. This device calculates a score based on various recordable driving-related events like abrupt braking or irregular turning actions. Our qualitative methodology incorporated semi-structured interviews and ethnographic fieldwork, in order to explore drivers' attitudes towards the system and its effect on driving behaviour and working conditions. Our findings illustrate how bus operators simultaneously accommodate and resist the demands Drivewell places upon them. Our work also demonstrates how this digital intervention acts in conjunction with other driver-related technologies, creating a unique digital ecosystem on the modern London bus. Our research contributes to HCI understandings of digital surveillance and performance monitoring in the modern workplace.

Trust and engagement in online health: a timeline approach

Abstract: This chapter explores the role of the Internet in health behavior placing particular emphasis on the issue of trust and trusting behaviors as this is seen as key to determining the impact of the Internet on health outcomes and behaviors. It examines the context of trust in relation to online health advice and information and presents a staged model of trust that helps reconcile differences in the literature. The chapter also presents a timeline approach to the study of trust and engagement in online health. It details the way in which health consumers are initially drawn to online resources through to their longer-term engagement and their influence upon health-based decision making. The chapter draws together the literature and the results of the work to present some conclusions and considerations for future research.

Using IMUs to identify supervisors on touch devices.

Abstract: In addition to their popularity as personal devices, tablets, are becoming increasingly prevalent in work and public settings. In many of these application domains a supervisor user – such as the teacher in a classroom – oversees the function of one or more devices. Access to supervisory functions is typically controlled through the use of a passcode, but experience shows that keeping this passcode secret can be problematic. We introduce SwipeID, a method of identifying supervisor users across a set of touch-based devices by correlating data from a wrist-worn inertial measurement unit (IMU) and a corresponding touchscreen interaction. This approach naturally supports access at the time and point of contact and does not require any additional hardware on the client devices. We describe the design of our system and the challenge-response protocols we have considered. We then present an evaluation study to demonstrate feasibility. Finally we highlight the potential for our scheme to extend to different application domains and input devices.

Crowdsourcing and CCTV: the Effect of Interface, Financial Bonus and Video Type

Abstract: Volunteer computing systems provide an easy mechanism for users who wish to perform large amounts of High Throughput Computing work. However, if the Volunteer Computing system is deployed over a shared set of computers where interactive users can seize back control of the computers this can lead to wasted computational effort and hence wasted energy. Determining on which resource to deploy a particular piece of work, or even to choose not to deploy the work at the current time, is a difficult problem to solve, depending both on the expected free time available on the computers within the Volunteer computing system and the expected runtime of the work - both of which are difficult to determine a-priori. We develop here a Reinforcement Learning approach to solving this problem and demonstrate that it can provide a reduction in energy consumption between 30% and 53% depending on whether we can tolerate an increase in the overheads incurred.

Assessing Patient Experience and Patient Preference when Designing Web Support for Smoking Cessation

Abstract: Patients will often resist campaigns to promote healthier behavior but the digital health revolution allows the creation of a much more nuanced set of health messages that can be tailored to the patient or end user In this study we explore the effects of patient preference on message acceptance and also explore what happens when messages are framed in terms of patient experience Smokers (n=113) viewed a quitting website in which material was expressed either as a factsheet or as patient experience (PEx) and where the material was either matched or unmatched to their own preferred quitting methods Across a range of measures, we found strong evidence that preference matching was effective in motivating smokers to engage with the material and we found modest support for the role of PEx in reducing message resistance

Automatic Identification of Personal Life Events in Twitter

Abstract: New social media has led to an explosion in personal digital data that encompasses both those expressions of self chosen by the individual as well as reflections of self provided by other, third parties. The resulting Digital Personhood (DP) data is complex and for many users it is too easy to become lost in the mire of digital data. This paper studies the automatic detection of personal life events in Twitter. Six relevant life events are considered from psychological research including: beginning school; first full time job; falling in love; marriage; having children and parent's death. We define a variety of features (user, content, semantic and interaction) to capture the characteristics of those life events and present the results of several classification methods to automatically identify these events in Twitter.