A primary well-controlled study of 900 participants found that personal presentation choices in professional emails (non-content changes like Profile Avatar 8 Signature) impact the recipient’s perception of the sender’s personality and the quality of the email itself. By understanding the role these choices play, employees can gain better control over how they influence the recipient of their messages. Results further indicate that although some variations can positively impact the recipient’s view of the sender, these same variations often also have negative side effects. This implies that many seemingly innocuous presentation decisions should be made in the context of who is receiving the email, and if these effects negatively impact the content of the message. For example, although statements in a Signature about the email having been written on a phone are included to preemptively apologize for typing mistakes, this causes the sender to appear less agreeable, less conscientious, and less open, and the email itself appears less well written and more poorly formatted. This is surprising given that the email itself was not changed in the study.

Web applications often need to present the user new information in the context of their current activity. Designers rely on a range of UI elements and visual techniques to present the new content to users, such as pop-ups, message icons, and marquees. Web designers need to select which technique to use depending on the centrality of the information and how quickly they need a reaction. However, designers often rely on intuition and anecdotes rather than empirical evidence to drive their decision-making as to which presentation technique to use. This work represents an attempt to quantify these presentation style decisions. We present a large (n=1505) user study that compares 15 visual attention-grabbing techniques with respect to reaction time, noticeability, annoyance, likability, and recall. We suggest glowing shadows and message icons with badges, as well as more possibilities for future work.

Information overload is a systemic problem for knowledge workers in enterprise. For a long time, information was scarce and therefore valuable. While, the explosion of digital information has made information plentiful, time to read and process that content is now scarce. This problem is only exacerbated by our increased mobility, and the expectation to be "on top" of the continuous barrage of documents while on the go. Knowledge workers in enterprise need solutions that are designed with quick methods for finding what to read in a large collection of documents (e.g. financial reports, legal documents, news), and ways of presenting it within small visual real estate. Unlike reviews, document collections are long, more varied, and context is extremely important. In response, we present Odin, a mobile web-based window onto a user's document corpus. Rather than performing corpus summarization, Odin users can quickly find opinions and documents that are Aligned or Divergent from the corpus' consensus, or those that are the most Relevant given the overall corpus' of opinions. Odin presents this information through a simple and intuitive mobile interface. To the authors' knowledge, this is the first UI/system (and support algorithm) to allow mobile users to place documents and their opinions in context through alignment rather than raw word count or sentiment. Positive results from two evaluations are also presented.

Email is the primary method of digital communication for most people, but the overwhelming quantity has led to a poverty of attention. Existing manual and automatic solutions that aim to save important emails from falling through the cracks have begun to address this problem, but may increase user workload, sacrifice efficiency, or fail to identify high value communications. In response, we developed MinEMail, an alert system that uses a text message (SMS) to remind and notify users of critical emails that may have been missed or forgotten. MinEMail provides an alert infrastructure as well as accurately labeling and predicting which emails are critical, and when and how they need to be addressed. To motivate our system, we also present an up-front study with 777 participants that aims to understand the state and limitations of email and SMS in enterprise. We conduct an experience sampling study of over 3000 emails in order to construct MinEMail's predictive models. Finally, we present the results from a 15 user ecologically valid real-world deployment of MinEMail in enterprise.

Pagination the process of determining where to break an article across pages in a multi-article layout is a common layout challenge for most commercially printed newspapers and magazines. To date, no one has created an algorithm that determines a minimal pagination break point based on the content of the article. Existing approaches for automatic multi-article layout focus exclusively on maximizing content (number of articles) and optimizing aesthetic presentation (e.g., spacing between articles). However, disregarding the semantic information within the article can lead to overly aggressive cutting, thereby eliminating key content and potentially confusing the reader, or setting too generous of a break point, thereby leaving in superfluous content and making automatic layout more difficult. This is one of the remaining challenges on the path from manual layouts to fully automated processes that still ensure article content quality. In this work, we present a new approach to calculating a document minimal break point for the task of pagination. Our approach uses a statistical language model to predict minimal break points based on the semantic content of an article. We then compare 4 novel candidate approaches, and 4 baselines (currently in use by layout algorithms). Results from this experiment show that one of our approaches strongly outperforms the baselines and alternatives. Results from a second study suggest that humans are not able to agree on a single "best" break point. Therefore, this work shows that a semantic-based lower bound break point prediction is necessary for ideal automated document synthesis within a real-world context.

A news article generally contains a high-level overview of the facts early on, followed by paragraphs of more detailed information. This structure allows copy editors to truncate the latter paragraphs of an article in order to satisfy space limitations without losing critical information. Existing approaches to this problem of automatic multi-article layout focus exclusively on maximizing content and aesthetics. However, no algorithm can determine how "good" a truncation point is based on the semantic content, or article readability. Yet, disregarding the semantic information within the article can lead to either overly aggressive cutting, thereby eliminating key content and potentially confusing the reader; conversely, it may set too generous of a truncation point, thus leaving in superfluous content and making automatic layout more difficult. This is one of the remaining challenges on the path from manual layouts to fully automated processes with high quality output. In this work, we present a new semantic-focused approach to rate the quality of a truncation point. We built models based on results from an extensive user study on over 700 news articles. Further results show that existing techniques over-cut content. We demonstrate the layout impact through a second evaluation that implements our models in the first layout approach that integrates both layout and semantic quality. The primary contribution of this work is the demonstration that semantic-based modeling is critical for high-quality automated document synthesis within a real-world context.

While email is a major conduit for information sharing in enterprise, there has been little work on exploring the files sent along with these messages -- attachments. These accompanying documents can be large (multiple megabytes), lengthy (multiple pages), and not optimized for the smaller screen sizes, limited reading time, and expensive bandwidth of mobile users. Thus, attachments can increase data storage costs (for both end users and email servers), drain users' time when irrelevant, cause important information to be missed when ignored, and pose a serious access issue for mobile users. To address these problems we created AttachMate, a novel email attachment summarization system. AttachMate can summarize the content of email attachments and automatically insert the summary into the text of the email. AttachMate also stores all files in the cloud, reducing file storage costs and bandwidth consumption. In this paper, the primary contribution is the AttachMate client/server architecture. To ground, support and validate the AttachMate system we present two upfront studies (813 participants) to understand the state and limitations of attachments, a novel algorithm to extract representative concept sentences (tested through two validation studies), and a user study of AttachMate within an enterprise.

While conducting research focused on individuals with impairments is vitally important, such experiments often have high costs (time and money), and researchers may be limited in the instructions they can give, or participant feedback they can gather (due to the impairment). We present how an impairment emulation system (ACES) can be used by researchers in the behavioral sciences. By repurposing this new technology within the context of a "traditional" psychology experiment, we were able to analyze impaired linguistic and communication in a manner that was not possible without a system such as ACES. Our experiment on 96 participants provided strong support for a theory in the aphasia psychology community, and uncovered new understandings of how people communicate when one interlocutor's speech is distorted with aphasia. These findings illustrate a new direction of HCI research that directly helps researchers in Psychology, Communication, and Speech and Hearing Science.

The ability of children to combine syllables represents an important developmental milestone. This ability is often delayed or impaired in a variety of clinical groups, including children with autism spectrum disorders (ASD) and speech delays (SPD). Prior work has demonstrated successful use of computer-based voice visualizations to facilitate speech production and vocalization in children with and without ASD/SPD. While prior work has focused on increasing frequency of speech-like vocalizations or accuracy of speech sound production, we believe that there is a potential new direction of research: exploration of real-time visualizations to shape multisyllabic speech. Over two years we developed VocSyl, a real-time voice visualization system. Rather than building visualizations based on what adult clinicians and software designers may think is needed, we designed VocSyl using the Task Centered User Interface Design (TCUID) methodology throughout the design process. Children with ASD and SPD, targeted users of the software, were directly involved in the development process, allowing us to focus on what these children demonstrate they require. This paper presents the results of our TCUID design cycle of VocSyl, as well as design guidelines for future work with children with ASD and SPD.

To an outsider it may appear as though an individual with aphasia has poor cognitive function. However, the problem resides in the individual's receptive and expressive language, and not in their ability to think. This misperception, paired with a lack of empathy, can have a direct impact on quality of life and medical care. Hailpern's 2011 paper on ACES demonstrated a novel system that enabled users (e.g., caregivers, therapists, family) to experience first hand the communication-distorting effects of aphasia. While their paper illustrated the impact of ACES on empathy, it did not validate the underlying distortion emulation. This paper provides a validation of ACES' distortions through a Turing Test experiment with participants from the Speech and Hearing Science community. It illustrates that text samples generated with ACES distortions are generally not distinguishable from text samples originating from individuals with aphasia. This paper explores ACES distortions through a `How Human' is it test, in which participants explicitly rate how human- or computer-like distortions appear to be.

It's not just what you say, but it is how you say it. To date, the majority of the Instant Message (IM) analysis and research has focused on the content of the conversation. The main research question has been, `what do people talk about?' focusing on topic extraction and topic modeling. While content is clearly critical for many real-world applications, we have largely ignored identifying `how' people communicate. Conversation structure and communication patterns provide deep insight into how conversations evolve, and how the content is shared. Motivated by theoretical work from psychology and linguistics in the area of conversation alignment, we introduce SCENE, an evolution network approach to extract knowledge from a conversation network. We demonstrate the potential of our approach by taking the task of matching conversation partners. We find that SCENE is more successful because, in contrast to existing approaches, SCENE treats a conversation as an evolving, rather than a static document, and focuses on the structural elements of the conversation instead of being tied to the specific content.

Individuals with aphasia, an acquired communication disorder, constantly struggle against a world that does not understand them. This lack of empathy and understanding negatively impacts their quality of life. While aphasic individuals may appear to have lost cognitive functioning, their impairment relates to receptive and expressive language, not to thinking processes. We introduce a novel system and model, Aphasia Characteristics Emulation Software (ACES), enabling users (e.g., caregivers, speech therapists and family) to experience, firsthand, the communication-distorting effects of aphasia. By allowing neurologically typical individuals to "walk in another's shoes," we aim to increase patience, awareness and understanding. ACES was grounded in the communication science and psychological literature, and informed by an initial pilot study. Results from an evaluation of 64 participants indicate that ACES provides a rich experience that increases understanding and empathy for aphasia.

According to cognitive science literature, human memory is predicated on contextual cues (e.g., room, music) in the environment. During recall tasks, we associate information/activities/objects with contextual cues. However, computer systems do not leverage our natural process of using contextual cues to facilitate recall. We present a new interaction technique, Pivoting, that allows users to search for contextually related activities and find a target piece of information (often not semantically related). A sample motivation for contextual search would be, 'what was that website I was looking at when Yesterday by The Beatles was last playing?' Our interaction technique is grounded in the cognitive science literature, and is demonstrated in our system YouPivot. In addition, we present a new personal annotation method, called TimeMarks, to further support contextual recall and the pivoting process. In a pilot study, participants were quicker to identify websites, and preferred using YouPivot, compared to current tools. YouPivot demonstrates how principles of human memory can be applied to enhance the search of digital information.

WINACS (Web-based Information Network Analysis for Computer Science) is a project that incorporates many recent, exciting developments in data sciences to construct a Web-based computer science information network and to discover, retrieve, rank, cluster, and analyze such an information network. With the rapid development of the Web, huge amounts of information are available in the form of Web documents, structures, and links. It has been a dream of the database and Web communities to harvest such information and reconcile the unstructured nature of the Web with the neat, semi-structured schemas of the database paradigm. Taking computer science as a dedicated domain, WINACS first discovers related Web entity structures, and then constructs a heterogeneous computer science information network in order to rank, cluster and analyze this network and support intelligent and analytical queries.

When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying high-utility applications is a critical first step for Task Analysis, Time Management/Workflow analysis, and Interruption research. However, existing techniques fail to identify at least 57% of these applications. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility without identifying task. In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. This model of computer usage is based upon 321 hours of real-world data from 22 users (both professional and academic). Unlike existing approaches, our model is not limited by a pre-existing set of applications or known tasks. We conclude with a discussion of the direct implications for improving accuracy in the fields of interruptions, task analysis, and time management systems.

The impact of living in a world that does not understand your impairment can be frustrating and a daunting task. Consider how an individual would feel if their family, friends, or doctors did not understand or were not even empathetic to daily struggles brought on by an acquired language disorder such as Aphasia. This work seeks to shed new light on aphasia by creating an instant message client which emulates the effects of aphasia. The goal of this new system is to raise awareness, teach, and increase empathy for caregivers, family members, and doctors/therapists who work with this population on a daily basis.

Communication disorders occur across the lifespan and encompass a wide range of conditions that interfere with individuals' abilities to hear (e.g., hearing loss), speak (e.g., voice disorders; motor speech disorders), and/or use language (e.g., specific language impairment; aphasia) to meet their communication needs. Such disorders often compromise the social, recreational, emotional, educational, and vocational aspects of an individual's life. This research examines the development and implementation of new software that facilitates multi-syllabic speech production in children with autism and speech delays. The VocSyl software package utilizes a suite of audio visualizations that represent a myriad of audio features in abstract representations. The goal of these visualizations is to provide children with language impairments a new persistent modality in which to experience and practice speech-language skills.

Real-time computer feedback systems (CFS) have been shown to impact the communication of neurologically typical individuals. Promising new research appears to suggest the same for the vocalization of low functioning children with Autistic Spectrum Disorder (ASD). The distinction between speech-like versus non-speech-like vocalizations has rarely, if ever, been addressed in the HCI community. This distinction is critical as we strive to most effectively and efficiently facilitate speech development in children with ASD, while simultaneously helping decrease vocalizations that do not facilitate positive social interactions. This paper provided an extension of Hailpern et al. in 2009 by examining the influence of a computerized feedback system on both the speech-like and non-speech-like vocalizations of five nonverbal children with ASD. Results were largely positive, in that some form of computerized feedback was able to differentially facilitate speech-like vocalizations relative to nonspeech-like vocalizations in 4 of the 5 children. The main contribution of this work is in highlighting the importance of distinguishing between speech-like versus nonspeech-like vocalizations in the design of feedback systems focused on facilitating speech in similar populations.

One hallmark difficulty of children with Autism Spectrum Disorder (ASD) centers on communication and speech. Research into computer visualizations of voice has been shown to influence conversational patterns and allow users to reflect upon their speech. In this paper, we present the Spoken Impact Project (SIP), an effort to examine the effect of audio and visual feedback on vocalizations in low-functioning children with ASD by providing them with additional means of understanding and exploring their voice. This research spans over 12 months, including the creation of multiple software packages and detailed analysis of more than 20 hours of experimental video. SIP demonstrates the potential of computer generated audio and visual feedback to encourage vocalizations of children with ASD.

With the advent of Web 2.0 technologies, websites have evolved from static pages to dynamic, interactive Web-based applications with the ability to replicate common desktop functionality. However, for blind and visually impaired individuals who rely upon screen readers, Web 2.0 applications force them to adapt to an inaccessible use model. Many technologies, including WAI-ARIA, AJAX, and improved screen reader support, are rapidly evolving to improve this situation. However, simply combining them does not solve the problems of screen reader users. The main contributions of this paper are two models of interaction for screen reader users, for both traditional websites and Web 2.0 applications. Further contributions are a discussion of accessibility difficulties screen reader users encounter when interacting with Web 2.0 applications, a user workflow design model for improving Web 2.0 accessibility, and a set of design requirements for developers to ease the user's burden and increase accessibility. These models, accessibility difficulties, and design implications are based directly on responses and lessons learned from usability research focusing on Web 2.0 usage and screen reader users. Without the conscious effort of Web engineers and designers, most blind and visually impaired users will shy away from using new Web 2.0 technology in favor of desktop based applications.

Due to the profile of strengths and weaknesses indicative of autism spectrum disorders (ASD), technology may play a key role in ameliorating communication difficulties with this population. This paper documents coding guidelines established through cross-disciplinary work focused on facilitating communication development in children with ASD using computerized feedback. The guidelines, referred to as A3 (pronounced A-Cubed) or Annotation for ASD Analysis, define and operationalize a set of dependent variables coded via video annotation. Inter-rater reliability data are also presented from a study currently in-progress, as well as related discussion to help guide future work in this area. The design of the A3 methodology is well-suited for the examination and evaluation of the behavior of low-functioning subjects with ASD who interact with technology.

Digital tools for annotation of video have the promise to provide immense value to researchers in disciplines ranging from psychology to ethnography to computer science. With traditional methods for annotation being cumbersome, time-consuming, and frustrating, technological solutions are situated to aid in video annotation by increasing reliability, repeatability, and workflow optimizations. Three notable limitations of existing video annotation tools are lack of support for the annotation workflow, poor representation of data on a timeline, and poor interaction techniques with video, data, and annotations. This paper details a set of design requirements intended to enhance video annotation. Our framework is grounded in existing literature, interviews with experienced coders, and ongoing discussions with researchers in multiple disciplines. Our model is demonstrated in a new system called VCode and VData. The benefit of our system is that is directly addresses the workflow and needs of both researchers and video coders.

Informal design tools can provide immense value during the creative stages of the design process, e.g., by transforming sketches into interactive simulations. Two key limitations of informal and many other design tools are that they do not promote working with multiple design ideas in parallel or collaboration. In this paper, we present a new interaction model that allows a team of designers to work efficiently with multiple ideas in parallel. The model is grounded in theories of creativity and collaboration, and was further informed by observations of creative group work practice. Our interaction model is fully demonstrated within a new system called TEAM STORM. Results from an initial evaluation indicate that design teams are able to effectively utilize our system to create, organize, and share multiple design ideas during creative group work. The benefit of our model is that it demonstrates how many existing single-user design tools can be extended to support working efficiently with multiple ideas in parallel and co-located collaboration.

The current state of software which targets older adults' ability to use computers focuses on physical issues while largely ignoring the cognitive issues. As a larger percentage of Americans are considered "old" (60+), the lack of a system tailored to the needs of this age demographic has resulted in a part of the population that is disconnected from the rest of the world. This paper describes WISE, an alternative OS and application UI that specifically targets the cognitive deficits of older adults.