This paper details our collaborative approach in capturing a holistic understanding of parental technology use through an assets-based framework. We steer the focus away from the design of technology as the central force of technological innovation, and instead support participants to reflect and describe intimate details that highlight specific use-contexts of technology in their lives. We leverage a group of foreign graduate student mothers' self-described unique strengths to gain an in-depth account of their lived experiences with technology. As research participants and co-authors, our collaborators elicit intimate narratives about meaningful events in their lives, bringing social and cultural aspects of their lived experience to the forefront, and thus providing broader context of their use of technology. We detail and reflect upon our approach of promoting user agency by creating an affinity group, fostering a safe and intimate space for research engagement, and describe the implications of using our adapted research methodology in intimate settings. We conclude by highlighting the various ways in which technology facilitates foreign student parenting, as well as the ways in which it serves as a temporary band-aid solution, prompting consideration of larger social issues.

Children in international and cross-cultural families in and outside of the US often learn and speak more than one language. Challenges can arise for these children in terms of communicating with other children and being able to fully participate in school and society using the primary country language, in developing relationships with distant relatives in other languages, and with the lack of opportunities for practising additional languages within a small community of speakers. Recent research shows that some parents use screen media content to acquaint their children with their parent’s native language, and to also help them become proficient in the language of communication in the country that they reside in. We leverage the qualities of screen media in aiding children with language learning, and try to translate those qualities into the design of a CUI for children to explore the potential of designing conversational user interfaces which can double as assistive language aids. By reviewing the relevant literature about the role of screen media content in young children’s language learning, and interviewing a subset of parents raising multilingual children, we present a preliminary list of objectives to guide the design of conversational user interfaces for young children’s bilingual language acquisition.

Telehealth rehabilitation systems aimed at providing physical and occupational therapy in the home face considerable challenges in terms of clinician and therapist buy-in, system and training costs, and patient and caregiver acceptance. Understanding the optimal workflow process to support practitioners in delivering quality care in partnership with assistive technologies is significant. We describe the iterative co-development of our hybrid physical/digital workflow process for assisting therapists with the setup and calibration of a computer vision based system for remote rehabilitation. Through an interdisciplinary collaboration, we present promising preliminary concepts for streamlining the translation of research outcomes into everyday healthcare experiences.

The struggle to thrive as a productive student researcher, an attentive parent, and a caring partner can be difficult, particularly for international student parents who are far from home and also possibly burdened with complex cultural expectations, interpersonal dynamics, and institutional biases. Using uses and gratifications theory as a framing mechanism, we describe interviews with twelve international student mothers in the United States who are primary caregivers of children between six months to five years old, focusing on the context of their use of screen media content and devices, the gratifications they seek from their children's use of screen media devices, and the differences in their perceptions about the use of screen media as an educated, non-US parent. Our findings give an initial account of the role of screen based technology in their domestic life with young children, and the limitations of their technological experience. We present four opportunities for designing for this population including technologies for positive distraction, interactive language aids, playful acquaintance tools, and anonymous peer networks for parent support. We conclude by formulating future promising avenues of research in this design space.

Design is commonly understood as a storytelling practice, yet we have few narratives with which to describe the felt experiences of struggle, pain, and difficulty, beyond treating them as subjects to resolve. This work uses the praxis of embodied design as a way to bring more complex narratives to the community for contemplation---to engage and entangle personal and difficult stories within a public context. We propose the term Design Memoirs for these first-person practices and reflections. Design Memoirs are subjective and corporeal in nature, and provide a direct and observable way to reckon with felt experiences through, and for, design. We demonstrate Design Memoirs by drawing on our own experiences as mothers, caregivers, and corporeal subjects. Following Barad, we propose a practice of diffractive reading to locate resonances between Design Memoirs which render difficult autobiographical material addressable, shareable, and open for new interpretations. We present this strategy as a method for arriving at deeper understandings of difficult experiences.

Physical rehabilitation typically requires therapists to make judgements about patient movement and functional improvement using subjective observation. This process makes it challenging to quantitatively track, compute and predict long-term patient improvement. We therefore propose a novel methodical approach to the standardized and interpretable quantification of patient movement during rehabilitation. We describe the expert-led development of a movement assessment rubric and an accompanying quantitative rating system. We present our movement capture and annotation computational tools designed to implement the rubric and assist therapists in the quantitative documentation and assessment of rehabilitation. We describe results from a movement capture study of the tool with nine stroke survivors and a movement rating study with four therapists. Findings from these studies highlight potential optimal methodical process paths for individuals engaged in capturing, understanding and predicting human movement performance.

Present day ideals of good parenting are socio-technical constructs formed at the intersection of medical best practices, cultural norms, and technical innovation. These ideals take shape in relation to the fundamental uncertainty that parents/mothers face, an uncertainty that comes from not knowing how to do what is best for one's children, families, and selves. The growing body of parent-focused smart devices and data-tracking platforms emerging from this intersection frame the responsible parent as one who evaluates, analyzes, and mitigates data-defined risks for their children and family. As these devices and platforms proliferate, whether from respected medical institutions or commercial interests, they place new demands on families and add an implicit emphasis on how humans (often mothers) can be augmented and improved by data-rich technology. This is expressed both in the actions they support (e.g., breastfeeding, monitoring food intake), as well as in the emotions they render marginal (e.g., rage, struggle, loss, and regret). In this article, we turn away from optimization and self-improvement narratives to attend to our own felt experiences as mothers and designers. Through an embodied practice of creating Design Memoirs, we speak directly to the HCI community from our position as both users and subjects of optimized parenting tools. Our goal in this work is to bring nuance to a domain that is often rendered in simplistic terms or frames mothers as figures who could endlessly do more for the sake of their families. Our Design Memoirs emphasize the conflicting and often negative emotions we experienced while navigating these tools and medical systems. They depict our feelings of being at once powerful and powerless, expressing rage and love simultaneously, and struggling between expressing pride and humility. The Design Memoirs serve us in advocating that designers should use caution when considering a problem/solution focus to the experiences of parents. We conclude by reflecting on how our shared practice of making memoirs, as well as other approaches within feminist and queer theory, suggest strategies that trouble these optimization and improvement narratives. Overall, we present a case for designing for mothers who feel like they are just making do or falling short, in order to provide relief from the anxiety of constantly seeking improvement.

Technostress is an emerging and significant psychological phenomenon associated with the use of technology. As humans increasingly encounter computational technology on a daily basis, there is a need to manage the anxieties and tensions that can result from these interactions. Using the lens of critical design, we created a design probe to explore this concept of technology induced stress. The probe builds on the topic of slow technology and embraces multisensory experiences as a tool for individuals to reflect on their relationship with technology.

The miniaturization of electronic technologies, as well as advances in organic and material science, have contributed to the development of composite, smart, and computational materials that create promising narratives for the future of ubiquitous computing. The goal of this one-day studio is to develop tools to acquire a deeper conceptual and critical understanding of materiality in HCI. The studio will draw on strategies from a broad range of sources including critical making, speculative design, experiential prototyping, and indigenous ontologies, in order to map out key questions and concerns. The studio will give the participants the opportunity to discuss the concept of Critical Materiality as a framework for developing tangible, embedded, and embodied interfaces, by brainstorming narratives around the past lives, current uses, and the future imaginaries of materials. Participants will co-develop a shared vocabulary and theoretical framework for Critical Materiality as a strategy to be deployed in conceiving and implementing HCI artifacts and experiences. The studio will culminate in the design and production of a deck of cards that propose keywords, questions, concerns, and opportunities for Hybrid Materials within this Critical Materiality framework. The deck of cards will be made available during the conference and distributed online.

Interactive home based rehabilitation therapy is a promising treatment development for stroke survivors. As the impairment characteristics of each stroke survivor are unique, interactive rehabilitation systems need to be customized to the functional and movement quality outcome goals of the patient, and adaptable over time as therapy progresses. In this paper, we present our iterative co-design process creating a set of modular therapy objects and a rehabilitation protocol for upper extremity stroke survivors. Our objects and training protocol are adaptable components within a computer vision based interactive system that captures and analyzes stroke survivors completing rehabilitation activities. We report on findings from a pilot study with nine stroke survivors and a workshop with five physiotherapists where we highlight challenges in designing objects for impaired grasps, opportunities for aligning objects with activities of everyday living, and the responsibility of design sensitivity.

As people generate large quantities of heterogeneous data across their lifetimes, there is an opportunity to consider how we might build digital systems that leverage this information to help people communicate aspects of their life for which they would like to be remembered without the need to directly assign or pass on this information to another person. We present a study that leverages existing research and the use of an online design probe to explore how people think about how they'll be remembered, and how digital systems and information might help shape how people look back on and interpret people's lives after they've passed away. Findings from this work articulate specific challenges and opportunities for building systems to support people's ability to engage with experiences and memories through their digital materials.

Delivering long term, unsupervised stroke rehabilitation in the home is a complex challenge that requires robust, low cost, scalable, and engaging solutions. We present HOMER, an interactive system that uses novel therapy artifacts, a computer vision approach, and a tablet interface to provide users with a flexible solution suitable for home based rehabilitation. HOMER builds on our prior work developing systems for lightly supervised rehabilitation use in the clinic, by identifying key features for functional movement analysis, adopting a simplified classification assessment approach, and supporting transferability of therapy outcomes to daily living experiences through the design of novel rehabilitation artifacts. A small pilot study with unimpaired subjects indicates the potential of the system in effectively assessing movement and establishing a creative environment for training.

Death is an inevitable part of life, but digital systems have been slow to address the complex issues that arise when a person passes away. As digital systems have become an increasingly important part people's lives, so too have these systems begun to play a role in a number of practices related to death, such as legacy-making, bereavement, and remembrance. In this paper, we conduct a survey of seventy-five digital systems designed to support these practices. Building on prior work, we analyzed these systems to derive findings that articulate how digital technologies reflect how people think about and engage with death. Based on these findings, we generated strategies designed to help system designers grapple with the complex needs that result from navigating death online.

As people increasingly turn to digital channels to share, store, and reflect on their lives and experiences, the processes by which they manage the diverse collection of information generated over the course of their lives are changing. These processes, once a matter of hands-on curation and personal meaning making, are now deeply rooted in interactions with digital systems. In this work, we drew from prior research from personalization, memory, and information management to create four interactive, provocative systems. Through sessions with 12 adults from Pittsburgh, PA we used a combination of these systems and interviews to examine how systems might play a role in the near and long term resurfacing of personal and familial digital information. Findings point to an opportunity to create systems that can openly mediate the curation and transmission of digital content, and ways to draw meaning from the differences between how systems and people recall and represent their experiences.

Multimedia social communication is becoming commonplace. Television is becoming smart and social; media sharing applications are transforming the way we converse and recall events and videoconferencing is a common application on our computers, phones, tablets and even televisions. The confluence of computer-mediated interaction, social networking, and multimedia content are radically reshaping social communications, bringing new challenges and opportunities. This workshop, in its third edition, provides an opportunity to explore socially-aware multimedia, in which the social dimension of mediated interactions between people are considered to be as important as the characteristics of the media content. Even though this social dimension is implicitly addressed in some current solutions, further research is needed to better understand what makes multimedia socially-aware.

In this article, we present a novel algorithm to discover multirelational structures from social media streams. A media item such as a photograph exists as part of a meaningful interrelationship among several attributes, including time, visual content, users, and actions. Discovery of such relational structures enables us to understand the semantics of human activity and has applications in content organization, recommendation algorithms, and exploratory social network analysis. We are proposing a novel nonnegative matrix factorization framework to characterize relational structures of group photo streams. The factorization incorporates image content features and contextual information. The idea is to consider a cluster as having similar relational patterns; each cluster consists of photos relating to similar content or context. Relations represent different aspects of the photo stream data, including visual content, associated tags, photo owners, and post times. The extracted structures minimize the mutual information of the predicted joint distribution. We also introduce a relational modularity function to determine the structure cost penalty, and hence determine the number of clusters. Extensive experiments on a large Flickr dataset suggest that our approach is able to extract meaningful relational patterns from group photo streams. We evaluate the utility of the discovered structures through a tag prediction task and through a user study. Our results show that our method based on relational structures, outperforms baseline methods, including feature and tag frequency based techniques, by 35%--420%. We have conducted a qualitative user study to evaluate the benefits of our framework in exploring group photo streams. The study indicates that users found the extracted clustering results clearly represent major themes in a group; the clustering results not only reflect how users describe the group data but often lead the users to discover the evolution of the group activity.

Presentation support tools, such as Microsoft PowerPoint, pose challenges both in terms of creating linear presentations from complex data and fluidly navigating such linear structures when presenting to diverse audiences. NextSlidePlease is a slideware application that addresses these challenges using a directed graph structure approach for authoring and delivering multimedia presentations. The application combines novel approaches for searching and analyzing presentation datasets, composing meaningfully structured presentations, and efficiently delivering material under a variety of time constraints. We introduce and evaluate a presentation analysis algorithm intended to simplify the process of authoring dynamic presentations, and a time management and path selection algorithm that assists users in prioritizing content during the presentation process. Results from two comparative user studies indicate that the directed graph approach promotes the creation of hyperlinks, the consideration of connections between content items, and a richer understanding of the time management consequences of including and selecting presentation material.

Lifelog collections digitally capture and preserve personal experiences and can be mined to reveal insights and understandings of individual significance. These rich data sources also offer opportunities for learning and discovery by motivated third parties. We employ a custom-designed storytelling application in constructing meaningful lifelog summaries from third-party perspectives. This storytelling initiative was implemented as a core component in a university media-editing course. We present promising results from a preliminary study conducted to evaluate the utility and potential of our approach in creatively interpreting a unique experiential dataset.

Contemporary distributed enterprises present challenges in terms of demonstrating community activity awareness and coherence across individuals and teams in collaborating networks. Building with a Memory is an experiential media system that captures and represents human activity in a distributed workplace over time. The system senses and analyzes movement in two workspaces in a mixed-use building with the results rendered in an informative ambient display in the building entryway. We describe the design and development of the system, together with insights from two studies of the installation and promising future directions.

This work aims at discovering community structure in rich media social networks through analysis of time-varying, multirelational data. Community structure represents the latent social context of user actions. It has important applications such as search and recommendation. The problem is particularly useful in the enterprise domain, where extracting emergent community structure on enterprise social media can help in forming new collaborative teams, in expertise discovery, and in the long term reorganization of enterprises based on collaboration patterns. There are several unique challenges: (a) In social media, the context of user actions is constantly changing and coevolving; hence the social context contains time-evolving multidimensional relations. (b) The social context is determined by the available system features and is unique in each social media platform; hence the analysis of such data needs to flexibly incorporate various system features. In this article we propose MetaFac (MetaGraph Factorization), a framework that extracts community structures from dynamic, multidimensional social contexts and interactions. Our work has three key contributions: (1) metagraph, a novel relational hypergraph representation for modeling multirelational and multidimensional social data; (2) an efficient multirelational factorization method for community extraction on a given metagraph; (3) an online method to handle time-varying relations through incremental metagraph factorization. Extensive experiments on real-world social data collected from an enterprise and the public Digg social media Web site suggest that our technique is scalable and is able to extract meaningful communities from social media contexts. We illustrate the usefulness of our framework through two prediction tasks: (1) in the enterprise dataset, the task is to predict users’ future interests on tag usage, and (2) in the Digg dataset, the task is to predict users’ future interests in voting and commenting on Digg stories. Our prediction significantly outperforms baseline methods (including aspect model and tensor analysis), indicating the promising direction of using metagraphs for handling time-varying social relational contexts.

Building with a Memory is a subtle responsive intervention that aims to provide cohesion and community awareness through the use of light and color. The installation delivers thought-provoking information by capturing, analyzing and rendering real-time and archived human activity in a workplace setting. The installation senses movement in the space through an IR camera and computer vision techniques. Two custom lighting fixtures and a video monitor render the aggregated movements. The visually simple aesthetic of the piece aims to balance active engagement and passive contribution, providing a rewarding experience for both occasional passersby and regular users of the space. This paper describes the motivations and contributions of the installation, together with insights gained from an informal evaluation and directions for future explorations.

This paper presents a novel social media summarization framework. Summarizing media created and shared in large scale online social networks unfolds challenging research problems. The networks exhibit heterogeneous social interactions and temporal dynamics. Our proposed framework relies on the co-presence of multiple important facets: who (users), what (concepts and media), how (actions) and when (time). First, we impose a syntactic structure of the social activity (relating users, media and concepts via specific actions) in our temporal multi-graph mining algorithm. Second, important activities along each facet are extracted as activity themes over time. Experiments on Flickr datasets demonstrate that our technique captures nontrivial evolution of media use in social networks.

Online social networking sites such as Flickr and Facebook provide a diverse range of functionalities that foster online communities to create and share media content. In particular, Flickr groups are increasingly used to aggregate and share photos about a wide array of topics or themes. Unlike photo repositories where images are typically organized with respect to static topics, the photo sharing process as in Flickr often results in complex time-evolving social and visual patterns. Characterizing such time-evolving patterns can enrich media exploring experience in a social media repository. In this paper, we propose a novel framework that characterizes distinct time-evolving patterns of group photo streams. We use a nonnegative joint matrix factorization approach to incorporate image content features and contextual information, including associated tags, photo owners and post times. In our framework, we consider a group as a mixture of themes - each theme exhibits similar patterns of image content and context. The theme extraction is to best explain the observed image content features and associations with tags, users and times. Extensive experiments on a Flickr dataset suggest that our approach is able to extract meaningful evolutionary patterns from group photo streams. We evaluate our method through a tag prediction task. Our prediction results outperform baseline methods, which indicate the utility of our theme based joint analysis.

This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the latent social context of user actions. It has important applications in information tasks such as search and recommendation. Social media has several unique challenges. (a) In social media, the context of user actions is constantly changing and co-evolving; hence the social context contains time-evolving multi-dimensional relations. (b) The social context is determined by the available system features and is unique in each social media website. In this paper we propose MetaFac (MetaGraph Factorization), a framework that extracts community structures from various social contexts and interactions. Our work has three key contributions: (1) metagraph, a novel relational hypergraph representation for modeling multi-relational and multi-dimensional social data; (2) an efficient factorization method for community extraction on a given metagraph; (3) an on-line method to handle time-varying relations through incremental metagraph factorization. Extensive experiments on real-world social data collected from the Digg social media website suggest that our technique is scalable and is able to extract meaningful communities based on the social media contexts. We illustrate the usefulness of our framework through prediction tasks. We outperform baseline methods (including aspect model and tensor analysis) by an order of magnitude.

In this video presentation, we introduce the Situated Multimedia Arts Learning Lab [SMALLab], a mixed-reality learning environment that supports interactive engagement through full body 3D movements and gestures within a collaborative, computationally mediated space. The video begins by describing the holistic approach to embodied and mediated learning developed by our transdisciplinary research team, grounded in understandings derived from research in the learning sciences, digital media and human computer interaction. We then outline the three core tenets of effective learning exemplified by our research -- embodiment, multimodality and collaboration. The video next demonstrates the design and functionality of the physical and digital components of SMALLab. We conclude by illustrating our partner collaborations with K12 teachers and students with four scenarios depicting Geography, Physics, Language Arts and Chemistry learning modules.

In this video presentation, we introduce NextSlidePlease, a novel slide authoring and presentation application. The video begins with a dramatization illustrating the shortcomings of existing slide-ware tools identified through our prior research. We then describe our theoretical framework for addressing these identified problems and present a dramatization of the process by which our NextSlidePlease application can be used to overcome such issues in a business context. In addition, we illustrate the novel functional aspects of our application algorithm that enable effective time management and flexible presentations. Finally, we present promising results from two user studies.

Transdisciplinary collaborations call for dynamic, responsive slide-ware presentations beyond the linear structure afforded by traditional tools. The NextSlidePlease application addresses this through a novel authoring and presentation interface. The application also features an innovative algorithm to enhance presentation time management. The cross-platform Java application is currently being evaluated in a variety of real-world presentation contexts.

Social media websites promote diverse user interaction on media objects as well as user actions with respect to other users. The goal of this work is to discover community structure in rich media social networks, and observe how it evolves over time, through analysis of multi-relational data. The problem is important in the enterprise domain where extracting emergent community structure on enterprise social media, can help in forming new collaborative teams, aid in expertise discovery, and guide long term enterprise reorganization. Our approach consists of three main parts: (1) a relational hypergraph model for modeling various social context and interactions; (2) a novel hypergraph factorization method for community extraction on multi-relational social data; (3) an on-line method to handle temporal evolution through incremental hypergraph factorization. Extensive experiments on real-world enterprise data suggest that our technique is scalable and can extract meaningful communities. To evaluate the quality of our mining results, we use our method to predict users' future interests. Our prediction outperforms baseline methods (frequency counts, pLSA) by 36-250% on the average, indicating the utility of leveraging multi-relational social context by using our method.

We present a framework for automatically summarizing social group activity over time. The problem is important in understanding large scale online social networks, which have diverse social interactions and exhibit temporal dynamics. In this work we construct summarization by extracting activity themes. We propose a novel unified temporal multi-graph framework for extracting activity themes over time. We use non-negative matrix factorization (NMF) approach to derive two interrelated latent spaces for users and concepts. Activity themes are extracted from the derived latent spaces to construct group activity summary. Experiments on real-world Flickr datasets demonstrate that our technique outperforms baseline algorithms such as LSI, and is additionally able to extract temporally representative activities to construct meaningful group activity summary.

Stories are one of the primary forms we use to organize our lived experiences into patterned narratives that aspire to communicate that which is memorable and valuable. SRMC 2008 provides a forum for multimedia researchers and practitioners to share their novel insights and understandings of the human and machine storytelling abilities necessary for the development of engaging, participatory and sustainable multimedia systems.