Abstract

Perhaps the term computer ‘memory’ has led people to believe that human memory has to be perfect and infallible. Many people worry when they realise they forget and some turn to recording and collecting as much as they can, e.g. photos or videos through life logging. Some people assume that by collecting they can avoid forgetting or at least have access to the information anytime later. And that is where they might be wrong. First of all, recordings are not equivalent to memories, and memories ‘can not be stored’. Secondly it has already been shown that people collect too much and organize too little for them to be able to find information later [1]. Thirdly, human memory works best when we forget… a lot.

What I want to talk about is my vision [2] that we can use design research to support human remembering by supporting our memory’s functions [3], which include a directive function (using the past to guide present and future thoughts and behaviours, e.g. solving problems), a self-representative function (creating a sense of self over time) and a social function (developing and nurturing relationships, through sharing of personal experiences). It is important to realise that in order to support these functions there is no need to improve our remembering capabilities, however it could benefit from the right type of support. Since remembering is a reconstructive process, individual memories are subject to change, continuously, and what someone experiences as a memory does not have to be the same as what happened or what other people remember from the experience.

Bits of information from the original experience can be used to stimulate and facilitate the reconstruction process. These so-called memory cues [4], which can be anything: from a photo, a song to a person or a location, are at the core of our research. We use a people-centred approach to study memory cues in everyday life, which informs the design of interactive systems that present these memory cues. Since these cues are often digital, while people prefer material objects [e.g. 5], we combine material and digital in our studies and designs.

1. Whittaker, S., Bergman, O., and Clough, P. Easy on that trigger dad: a study of long term family photo retrieval. Personal and Ubiquitous Computing 14,1 (2010), 31-43.
2. Hoven, E. van den. A future-proof past: Designing for remembering experiences. Memory Studies 7, 3 (2014), 373-387.
3. Bluck, S., Alea, N., Habermas, T., and Rubin, D. C. A tale of three functions: The self–reported uses of autobiographical memory. Social Cognition 23, 1 (2005), 91-117.
4. Hoven, E. van den, and Eggen, B. The Cue is Key: Design for Real-Life Remembering. Zeitschrift für Psychologie 222, 2 (2014), 110-117.
5. Golsteijn, C., Hoven, E. van den, Frohlich, D., and Sellen, A. Towards a More Cherishable Digital Object. In Proc. DIS 2012, ACM Press (2012), 655-664.

Bio

Professor Dr Elise van den Hoven MTD is full Professor in the School of Software, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS) and part-time Associate Professor in the Department of Industrial Design, Eindhoven University of Technology (TU/e). She has two honorary appointments: Honorary Senior Research Fellow in Duncan of Jordanstone College of Art and Design, University of Dundee and Associate Investigator with the Australian Research Council’s Centre of Excellence in Cognition and its Disorders.

Her research interests span different disciplines, including human-computer interaction, design and psychology, including people-centred design, designing interactive systems, physical interaction and supporting human remembering.

Professor Van den Hoven leads the international research programme Materialising Memories, a collaboration between UTS, TU/e and the University of Dundee, which uses a design research approach to study people in their everyday remembering activities in order to come up with ways to support them.

www.elisevandenhoven.com
www.materialisingmemories.com

Abstract

Visualising dynamic graphs is important for many application areas.  For social media networks, they can help us understand the interaction and interests of users online.  In biology, they can illustrate the interactions between genes and biological processes.  Understanding and designing effective visualisation methods for dynamic network data is fundamental to these areas as well as many others.  In this talk, we focus on the effective presentation of dynamic networks.  In particular, we summarise recent results on dynamic graph visualisation with respect to animation (presentation of interactive movies of the data), small multiples (presenting the data through several linked windows like a comic book), and drawing stability (the visual stability of the data presentation).  We conclude with some recent work on scalable graph visualisation and in the visualisation of sets and their intersections.

Biography

Daniel Archambault has been working in the field of information visualization for ten years. His work in this area has focused on the development and evaluation of techniques for visualizing dynamic networks and scalable graph visualizations.  His research has been been applied to many areas outside of computer science, including the digital humanities, biology, networking, sociology, and social media analysis.

Abstract

In this talk I will present experiences and insights from our studies involving locative media, local history and community. Our work in the village of Wray has involved the longitudinal and ‘in the wild’ deployment of ‘digital noticeboard’ displays (conceived as technology probes) that support the sharing of photos/images. A significant portion of the submitted photo content relates to Wray’s local history and features of Wray’s landscape. Residents of the village have helped shape the system through involvement in co-design workshops. A key motivation of our current studies (as part of the SHARC project) is to explore issues around the co-curation of locative media experiences. A field trial (involving both residents and visitors) and a design workshop revealed both opportunities and challenges for the co-curation approach.

Bio

Dr Keith Cheverst is a Reader in HCI at Lancaster University where he obtained his PhD in 1999. Keith has also held the position of visiting scientist at Newcastle University’s Culture Lab, at Microsoft Research, Cambridge (working with the Socio-Digital systems group), and at the University of Melbourne (Department of Computing and Information Systems).

Keith’s primary research focus is in exploring the obdurate problems associated with the user-centered design of interactive systems in complex or semi-wild settings and the deployment and longitudinal study of these systems in order to gain insights into issues of user adoption and appropriation. He is particularly interested in the design interactive systems that feature locative media and associated mobile/pervasive technologies

The School of Computer Science is delighted to welcome Alan Mislove from Northeastern University Boston to give his talk on ‘Measuring Personalization of Online Services

Abstract: Today, many web services personalize their content, including Netflix (movie recommendations), Amazon (product suggestions), and Yelp (business reviews). In many cases, personalization provides advantages for users: for example, when a user searches for an ambiguous query such as “router,” Amazon may be able to suggest the woodworking tool instead of the networking device. However, personalization is rarely transparent (or even labeled), and has the potential be used to the user’s disadvantage. For example, on e-commerce sites, personalization could be used to manipulate the set of products shown (price steering) or by customizing the prices of products (price discrimination). Unfortunately, today, we lack the tools and techniques necessary to be able to detect when personalization is occurring, as well as what inputs are used to perform personalization.

In this talk, I discuss my group’s recent work that aims to address this problem. First, we develop a methodology for accurately measuring when web services are personalizing their content. While conceptually simple, there are numerous details that our methodology must handle in order to accurately attribute differences in results to personalization (as opposed to other sources of noise). Second, we apply this methodology to two domains: Web search services (e.g., Google, Bing) and e-commerce sites (e.g., BestBuy.com, Expedia). We find evidence of personalization for real users on both Google search and nine of the popular e-commerce sites. Third, using fake accounts, we investigate the effect of user attributes and behaviors on personalization; we find that the choice of browser, logging in, and a user’s previously content can significantly affect the results presented.

Bio: Alan Mislove is an Associate Professor at the College of Computer and Information Science at Northeastern University. He received his Ph.D. from Rice University in 2009. Prof. Mislove’s research concerns distributed systems and networks, with a focus on using social networks to enhance the security, privacy, and efficiency of newly emerging systems. He is a recipient of an NSF CAREER Award (2011), and his work has been covered by the Wall Street Journal, the New York Times, and the CBS Evening News.

This seminar is part of our ongoing series from researchers in HCI. See here for our current schedule.