Компьютеры: прочее
Различные книги в жанре Компьютеры: прочееResearching Serendipity in Digital Information Environments
Chance, luck, and good fortune are the usual go-to descriptors of serendipity, a phenomenon aptly often coupled with famous anecdotes of accidental discoveries in engineering and science in modern history such as penicillin, Teflon, and Post-it notes. Serendipity, however, is evident in many fields of research, in organizations, in everyday life—and there is more to it than luck implies. While the phenomenon is strongly associated with in person interactions with people, places, and things, most attention of late has focused on its preservation and facilitation within digital information environments. Serendipity's association with unexpected, positive user experiences and outcomes has spurred an interest in understanding both how current digital information environments support serendipity and how novel approaches may be developed to facilitate it. Research has sought to understand serendipity, how it is manifested in people's personality traits and behaviors, how it may be facilitated in digital information environments such as mobile applications, and its impacts on an individual, an organizational, and a wider level. Because serendipity is expressed and understood in different ways in different contexts, multiple methods have been used to study the phenomenon and evaluate digital information environments that may support it. This volume brings together different disciplinary perspectives and examines the motivations for studying serendipity, the various ways in which serendipity has been approached in the research, methodological approaches to build theory, and how it may be facilitated. Finally, a roadmap for serendipity research is drawn by integrating key points from this volume to produce a framework for the examination of serendipity in digital information environments.
Social Monitoring for Public Health
Public health thrives on high-quality evidence, yet acquiring meaningful data on a population remains a central challenge of public health research and practice. Social monitoring, the analysis of social media and other user-generated web data, has brought advances in the way we leverage population data to understand health. Social media offers advantages over traditional data sources, including real-time data availability, ease of access, and reduced cost. Social media allows us to ask, and answer, questions we never thought possible. This book presents an overview of the progress on uses of social monitoring to study public health over the past decade. We explain available data sources, common methods, and survey research on social monitoring in a wide range of public health areas. Our examples come from topics such as disease surveillance, behavioral medicine, and mental health, among others. We explore the limitations and concerns of these methods. Our survey of this exciting new field of data-driven research lays out future research directions.
Research in the Wild
The phrase «in-the-wild» is becoming popular again in the field of human-computer interaction (HCI), describing approaches to HCI research and accounts of user experience phenomena that differ from those derived from other lab-based methods. The phrase first came to the forefront 20-25 years ago when anthropologists Jean Lave (1988), Lucy Suchman (1987), and Ed Hutchins (1995) began writing about cognition being in-the-wild. Today, it is used more broadly to refer to research that seeks to understand new technology interventions in everyday living. A reason for its resurgence in contemporary HCI is an acknowledgment that so much technology is now embedded and used in our everyday lives. Researchers have begun following suit—decamping from their usability and living labs and moving into the wild; carrying out in-situ development and engagement, sampling experiences, and probing people in their homes and on the streets. The aim of this book is to examine what this new direction entails and what it means for HCI theory, practice, and design. The focus is on the insights, demands and concerns. But how does research in the wild differ from the other applied approaches in interaction design, such as contextual design, action research, or ethnography? What is added by labeling user research as being in-the-wild? One main difference is where the research starts and ends: unlike user-centered, and more specifically, ethnographic approaches which typically begin by observing existing practices and then suggesting general design implications or system requirements, in-the-wild approaches create and evaluate new technologies and experiences in situ (Rogers, 2012). Moreover, novel technologies are often developed to augment people, places, and settings, without necessarily designing them for specific user needs. There has also been a shift in design thinking. Instead of developing solutions that fit in with existing practices, researchers are experimenting with new technological possibilities that can change and even disrupt behavior. Opportunities are created, interventions installed, and different ways of behaving are encouraged. A key concern is how people react, change and integrate these in their everyday lives. This book outlines the emergence and development of research in the wild. It is structured around a framework for conceptualizing and bringing together the different strands. It covers approaches, methods, case studies, and outcomes. Finally, it notes that there is more in the wild research in HCI than usability and other kinds of user studies in HCI and what the implications of this are for the field.
Digital Forensic Science
Digital forensic science , or digital forensics , is the application of scientific tools and methods to identify, collect, and analyze digital (data) artifacts in support of legal proceedings. From a more technical perspective, it is the process of reconstructing the relevant sequence of events that have led to the currently observable state of a target IT system or (digital) artifacts. Over the last three decades, the importance of digital evidence has grown in lockstep with the fast societal adoption of information technology, which has resulted in the continuous accumulation of data at an exponential rate. Simultaneously, there has been a rapid growth in network connectivity and the complexity of IT systems, leading to more complex behavior that needs to be investigated. The goal of this book is to provide a systematic technical overview of digital forensic techniques, primarily from the point of view of computer science. This allows us to put the field in the broader perspective of a host of related areas and gain better insight into the computational challenges facing forensics, as well as draw inspiration for addressing them. This is needed as some of the challenges faced by digital forensics, such as cloud computing, require qualitatively different approaches; the sheer volume of data to be examined also requires new means of processing it.
